-------------------------------------------------------------------------------------------------------------
      name:  <unnamed>
       log:  C:\Users\muttermark laptop\Documents\stata\intersection\PAR_Replication\par_replication_062723.l
> og
  log type:  text
 opened on:  27 Jun 2023, 20:05:47

. version 16.1 // set version

. clear all // clear memory

. 
. /* Load data set*/
. use par_asap.dta

. 
. set scheme tufte

. 
. 
. ***Gen Gender Race Variable ***
. 
. gen intersection=0 if k_4a==1 & k_3a==1
(4,393 missing values generated)

. replace intersection=1 if k_4a==1 & k_3a==2
(1,306 real changes made)

. replace intersection=2 if  k_4a==0 & k_3a==1
(660 real changes made)

. replace intersection=3 if  k_4a==0 & k_3a==2
(188 real changes made)

. 
. label define mintersection 0"White Man"  1"White Woman" 2"Man of Color" 3"Woman of Color"

. 
. label value intersection mintersection

. 
. 
. rename a_2a civil_service 

. label var civil_service "Civil Servant"

. rename a_8a weekly_hours

. label var weekly_hours "Average Weekley Hours Worked"

. rename j_1a years_employ_state

. label var years_employ_state  "Years Employed in State Gov."

. rename j_1b years_employ_agency

. label var years_employ_agency  "Years Employed in Agency"

. rename j_1c years_employ_position 

. label var years_employ_position  "Years Employed in Position"

. gen age_2 = k_2a*k_2a
(490 missing values generated)

. label var age_2 "Age-squared"

. gen age = sqrt(age_2)
(490 missing values generated)

. label var age "Age"

. gen pid5= 1 if k_8b==2
(9,130 missing values generated)

. replace pid5= 2 if k_8b==4
(748 real changes made)

. replace pid5= 3 if k_8b==5
(1,210 real changes made)

. replace pid5= 4 if k_8b==3
(868 real changes made)

. replace pid5= 5 if k_8b==1
(3,880 real changes made)

. label var pid5 "Party ID"

. label define mpid5 1"Republican"  2"Lean Republican" 3"Independant" 4"Lean Democratic" 5"Democratic"

. 
. label value pid5 mpid5

. 
. 
. rename k_16a edu

. label var edu "Education"

. 
. rename a_3b agency_size

. label var agency_size "Total Agency Employees"

. 
. rename a_4b agency_budget 

. gen log_agency_budget = ln(1+agency_budget) 
(773 missing values generated)

. label var log_agency_budget "ln(Agency Budget, $2018)"

. 
. revrs e_1a 

. revrs e_1b 

. revrs e_1c 

. revrs e_1d 

. 
. label var reve_1a "Gov."

. label var reve_1b "Gov. Staff"

. label var reve_1c "Legis."

. label var reve_1d "Legis. Staff"

. 
. fsum reve_1a reve_1b reve_1c reve_1d  intersection civil_service weekly_hours age age_2 edu years_employ_st
> ate years_employ_agency years_employ_position pid5 agency_size log_agency_budget, stats(n mean sd min media
> n max) catvar(  intersection)

              Variable |        N     Mean       SD   Median      Min      Max                                                                                                                     
-----------------------+------------------------------------------------------
               reve_1a |     9276     2.44     1.04     2.00     1.00     5.00  
               reve_1b |     7754     3.37     1.11     3.50     1.00     5.00  
               reve_1c |     9319     3.25     1.01     3.00     1.00     5.00  
               reve_1d |     7708     3.13     1.00     3.00     1.00     5.00  
          intersection |     9280     0.34     0.70     0.00     0.00     3.00  
        White Man (%)  |     7126    76.79
      White Woman (%)  |     1306    14.07
     Man of Color (%)  |      660     7.11
   Woman of Color (%)  |      188     2.03
         civil_service |    10870     0.25     0.43     0.00     0.00     1.00  
          weekly_hours |     9249    51.70     8.86    50.00     0.00    80.00  
                   age |    11029    49.84     9.44    50.00    24.00    87.00  
                 age_2 |    11029  2572.86   952.57  2500.00   576.00  7569.00  
                   edu |    11328     4.10     1.17     5.00     1.00     5.00  
    years_employ_state |    11167    14.08    10.11    12.00     0.00    52.00  
   years_employ_agency |    10213    10.81     9.57     7.00     0.00    52.00  
 years_employ_position |    10193     5.26     5.12     4.00     0.00    50.00  
                  pid5 |     9095     3.34     1.68     4.00     1.00     5.00  
           agency_size |    11341     2.81     1.44     3.00     1.00     6.00  
     log_agency_budget |    10746     3.30     2.01     2.97     0.00     9.96  

. 
. *for table alt 1
. *drop if state== 27 | state==34 | state==45 
. *for table alt 2
. *drop if state==11
. 
. **** CODE USED TO PRODUCE TABLE 1*******
. 
. fsum reve_1a reve_1b reve_1c reve_1d  d_15a d_16a d_20a d_21a intersection civil_service weekly_hours age a
> ge_2 edu years_employ_state years_employ_agency years_employ_position pid5 agency_size log_agency_budget, u
> selabel stats(min median max) catvar(reve_1a reve_1b reve_1c reve_1d d_15a d_16a d_20a d_21a intersection c
> ivil_service edu) 

                                            Variable |        N     Mean   Median      Min      Max                                                                                                                              
-----------------------------------------------------+---------------------------------------------
                                                Gov. |     9276     2.44     2.00     1.00     5.00  
                                          Never (%)  |     1628    17.55
                              Less than Monthly (%)  |     3913    42.18
                                        Monthly (%)  |     2004    21.60
                                         Weekly (%)  |     1488    16.04
                                          Daily (%)  |      243     2.62
                                          Gov. Staff |     7754     3.37     3.50     1.00     5.00  
                                          Never (%)  |      208     2.68
                              Less than Monthly (%)  |     1896    24.45
                                        Monthly (%)  |     1773    22.87
                                         Weekly (%)  |     2554    32.94
                                          Daily (%)  |     1323    17.06
                                              Legis. |     9319     3.25     3.00     1.00     5.00  
                                          Never (%)  |      127     1.36
                              Less than Monthly (%)  |     2503    26.86
                                        Monthly (%)  |     2669    28.64
                                         Weekly (%)  |     2999    32.18
                                          Daily (%)  |     1021    10.96
                                        Legis. Staff |     7708     3.13     3.00     1.00     5.00  
                                          Never (%)  |      191     2.48
                              Less than Monthly (%)  |     2208    28.65
                                        Monthly (%)  |     2338    30.33
                                         Weekly (%)  |     2340    30.36
                                          Daily (%)  |      631     8.19
        Influence on Major Policy Changes - Governor |     7714     2.40     3.00     0.00     3.00  
                                           None (%)  |      244     3.16
                                         Slight (%)  |      965    12.51
                                       Moderate (%)  |     1996    25.88
                                           High (%)  |     4509    58.45
     Influence on Major Policy Changes - Legislature |     7701     2.30     2.00     0.00     3.00  
                                           None (%)  |      159     2.06
                                         Slight (%)  |     1053    13.67
                                       Moderate (%)  |     2787    36.19
                                           High (%)  |     3702    48.07
    Influence on Agency Rules/Regulations - Governor |     7642     1.82     2.00     0.00     3.00  
                                           None (%)  |      661     8.65
                                         Slight (%)  |     2328    30.46
                                       Moderate (%)  |     2413    31.58
                                           High (%)  |     2240    29.31
 Influence on Agency Rules/Regulations - Legislature |     7635     1.83     2.00     0.00     3.00  
                                           None (%)  |      468     6.13
                                         Slight (%)  |     2369    31.03
                                       Moderate (%)  |     2770    36.28
                                           High (%)  |     2028    26.56
                                        intersection |     9280     0.34     0.00     0.00     3.00  
                                      White Man (%)  |     7126    76.79
                                    White Woman (%)  |     1306    14.07
                                   Man of Color (%)  |      660     7.11
                                 Woman of Color (%)  |      188     2.03
                                       Civil Servant |    10870     0.25     0.00     0.00     1.00  
                                             No (%)  |     8188    75.33
                                            Yes (%)  |     2682    24.67
                        Average Weekley Hours Worked |     9249    51.70    50.00     0.00    80.00  
                                                 Age |    11029    49.84    50.00    24.00    87.00  
                                         Age-squared |    11029  2572.86  2500.00   576.00  7569.00  
                                           Education |    11328     4.10     5.00     1.00     5.00  
                            High school or less (%)  |      371     3.28
                                   Some college (%)  |      968     8.55
                              Bachelor's degree (%)  |     2109    18.62
                                 Graduate study (%)  |     1631    14.40
                                Graduate degree (%)  |     6249    55.16
                        Years Employed in State Gov. |    11167    14.08    12.00     0.00    52.00  
                            Years Employed in Agency |    10213    10.81     7.00     0.00    52.00  
                          Years Employed in Position |    10193     5.26     4.00     0.00    50.00  
                                            Party ID |     9095     3.34     4.00     1.00     5.00  
                              Total Agency Employees |    11341     2.81     3.00     1.00     6.00  
                            ln(Agency Budget, $2018) |    10746     3.30     2.97     0.00     9.96  

. 
. **** TABLE EXPORETED AND FORMATTED IN EXCEL ****
. 
. ***** CODE USED TO PRODUCE TABLE 2 ******
. 
. ologit reve_1a i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r , r 

Iteration 0:   log pseudolikelihood = -10356.699  
Iteration 1:   log pseudolikelihood = -8819.4854  
Iteration 2:   log pseudolikelihood = -8749.2319  
Iteration 3:   log pseudolikelihood = -8749.0873  
Iteration 4:   log pseudolikelihood = -8749.0873  

Ordered logistic regression                     Number of obs     =      7,515
                                                Wald chi2(93)     =    2873.27
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -8749.0873               Pseudo R2         =     0.1552

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.2422217   .0706904    -3.43   0.001    -.3807723   -.1036711
                     Man of Color  |  -.1357595   .1014439    -1.34   0.181    -.3345859    .0630669
                   Woman of Color  |  -.5274129   .1688884    -3.12   0.002    -.8584282   -.1963977
                                   |
                     civil_service |
                              Yes  |   -.971733   .0600389   -16.19   0.000    -1.089407   -.8540589
                      weekly_hours |   .0521346   .0031106    16.76   0.000     .0460381    .0582312
                               age |  -.0374195   .0224833    -1.66   0.096    -.0814859    .0066468
                             age_2 |     .00053   .0002215     2.39   0.017     .0000957    .0009642
                                   |
                               edu |
              High school or less  |   .0306371   .1979765     0.15   0.877    -.3573896    .4186638
                     Some college  |   .1162062   .1062374     1.09   0.274    -.0920154    .3244277
                   Graduate study  |   .0538401    .077269     0.70   0.486    -.0976045    .2052846
                  Graduate degree  |  -.0971884   .0647571    -1.50   0.133    -.2241101    .0297332
                                   |
                years_employ_state |   -.000374   .0041522    -0.09   0.928    -.0085121    .0077642
               years_employ_agency |  -.0313019    .004373    -7.16   0.000    -.0398728    -.022731
             years_employ_position |   .0076163   .0054818     1.39   0.165    -.0031279    .0183605
                                   |
                              pid5 |
                       Republican  |    .481098   .0819153     5.87   0.000     .3205471     .641649
                  Lean Republican  |   .1207507   .1017217     1.19   0.235    -.0786201    .3201215
                  Lean Democratic  |  -.0231355   .0978389    -0.24   0.813    -.2148963    .1686252
                       Democratic  |    .473495   .0747023     6.34   0.000     .3270812    .6199088
                                   |
                       agency_size |
                           25-100  |   .1619845   .0731383     2.21   0.027     .0186361    .3053329
                          101-500  |   .5105166   .0842327     6.06   0.000     .3454235    .6756097
                        501-1,000  |   .7649114   .1109232     6.90   0.000     .5475059    .9823169
                      1,001-5,000  |   1.068553   .1151358     9.28   0.000     .8428913    1.294215
                       Over 5,000  |   1.494491   .1556228     9.60   0.000     1.189476    1.799506
                                   |
                 log_agency_budget |   .1757835   .0201581     8.72   0.000     .1362744    .2152926
                      inst6017_nom |  -.0030011   .0028368    -1.06   0.290    -.0085611     .002559
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .6925461   .1617936     4.28   0.000     .3754364    1.009656
                Staff: Non-Fiscal  |  -.2202206    .157977    -1.39   0.163    -.5298497    .0894086
Income Security & Social Services  |   -1.47653    .136935   -10.78   0.000    -1.744918   -1.208143
                        Education  |  -.9776317   .1461753    -6.69   0.000     -1.26413   -.6911333
                           Health  |  -1.648944   .1473031   -11.19   0.000    -1.937653   -1.360235
                Natural Resources  |  -.7923242   .1261825    -6.28   0.000    -1.039637   -.5450112
             Environment & Energy  |  -.7873803   .1351057    -5.83   0.000    -1.052183   -.5225781
             Economic Development  |   .0223083   .1390922     0.16   0.873    -.2503073     .294924
                 Criminal Justice  |  -.9552778   .1347269    -7.09   0.000    -1.219338   -.6912179
                       Regulatory  |  -1.257715   .1303817    -9.65   0.000    -1.513259   -1.002172
                   Transportation  |    -1.0062   .1410028    -7.14   0.000    -1.282561     -.72984
                            Other  |   -.757503    .137055    -5.53   0.000    -1.026126   -.4888801
                                   |
                             state |
                               AK  |  -.3341416   .2197752    -1.52   0.128    -.7648931    .0966098
                               AZ  |  -1.072071   .2452188    -4.37   0.000    -1.552691   -.5914514
                               AR  |  -.2319074   .2038058    -1.14   0.255    -.6313594    .1675447
                               CA  |  -2.499601   .2436337   -10.26   0.000    -2.977114   -2.022088
                               CO  |  -.0331212   .2128896    -0.16   0.876    -.4503771    .3841348
                               CT  |  -1.157115   .2515839    -4.60   0.000     -1.65021   -.6640194
                               DE  |   -.367357   .2112314    -1.74   0.082     -.781363    .0466489
                               FL  |  -1.685318   .2436817    -6.92   0.000    -2.162925   -1.207711
                               GA  |  -.9216965   .2307668    -3.99   0.000    -1.373991   -.4694019
                               HI  |  -.7774421   .2439012    -3.19   0.001     -1.25548   -.2994046
                               ID  |   .2447971   .2047634     1.20   0.232    -.1565316    .6461259
                               IL  |  -1.432487   .2441575    -5.87   0.000    -1.911027   -.9539475
                               IN  |  -.5692946    .230641    -2.47   0.014    -1.021343   -.1172465
                               IA  |  -.2820726   .1985466    -1.42   0.155    -.6712168    .1070717
                               KS  |  -.4032152    .227537    -1.77   0.076    -.8491795    .0427492
                               KY  |  -1.063754   .2289834    -4.65   0.000    -1.512553   -.6149547
                               LA  |  -.8155946   .2608939    -3.13   0.002    -1.326937   -.3042519
                               ME  |  -.0783662   .2253939    -0.35   0.728    -.5201302    .3633978
                               MD  |  -.9876069   .2317822    -4.26   0.000    -1.441892   -.5333221
                               MA  |  -1.693045   .2448103    -6.92   0.000    -2.172865   -1.213226
                               MI  |   -.874717     .21754    -4.02   0.000    -1.301088   -.4483464
                               MN  |  -1.107307   .2253961    -4.91   0.000    -1.549075   -.6655391
                               MS  |  -.2822958   .2248794    -1.26   0.209    -.7230512    .1584597
                               MO  |  -1.220202   .2130826    -5.73   0.000    -1.637836   -.8025675
                               MT  |   .1358397   .2015739     0.67   0.500    -.2592379    .5309173
                               NE  |   .1869023   .2290752     0.82   0.415     -.262077    .6358815
                               NV  |  -.2360691   .2123013    -1.11   0.266     -.652172    .1800339
                               NH  |  -.0685534   .2225901    -0.31   0.758    -.5048219    .3677151
                               NJ  |  -1.228063   .2328847    -5.27   0.000    -1.684509   -.7716174
                               NM  |   .0465281   .2273325     0.20   0.838    -.3990354    .4920916
                               NY  |  -2.188579   .2690821    -8.13   0.000    -2.715971   -1.661188
                               NC  |  -1.032744   .1957113    -5.28   0.000    -1.416331   -.6491567
                               ND  |   .6604772    .205922     3.21   0.001     .2568774    1.064077
                               OH  |  -1.235707   .2358003    -5.24   0.000    -1.697867   -.7735465
                               OK  |  -.6671675   .2154399    -3.10   0.002    -1.089422   -.2449129
                               OR  |  -.2735063   .2181166    -1.25   0.210     -.701007    .1539945
                               PA  |  -1.880874   .2278246    -8.26   0.000    -2.327402   -1.434346
                               RI  |   .2145086    .226937     0.95   0.345    -.2302797    .6592969
                               SC  |  -.5503567   .2137538    -2.57   0.010    -.9693065   -.1314069
                               SD  |   .3450091   .2136162     1.62   0.106     -.073671    .7636891
                               TN  |  -1.180326   .2327253    -5.07   0.000    -1.636459   -.7241927
                               TX  |  -1.979577   .2153058    -9.19   0.000    -2.401568   -1.557585
                               UT  |   .0487906   .2036328     0.24   0.811    -.3503224    .4479036
                               VT  |    .260382   .2111284     1.23   0.217    -.1534221     .674186
                               VA  |  -1.115041   .2323401    -4.80   0.000    -1.570419   -.6596628
                               WA  |  -.9946893   .2303605    -4.32   0.000    -1.446187   -.5431911
                               WV  |  -.5057771   .2176936    -2.32   0.020    -.9324488   -.0791055
                               WI  |  -.4418259   .2162913    -2.04   0.041    -.8657491   -.0179028
                               WY  |   .5443989   .1957128     2.78   0.005     .1608089    .9279889
                                   |
                              year |
                             1978  |  -.6629782    .087449    -7.58   0.000    -.8343751   -.4915813
                             1984  |   -.673541   .0838074    -8.04   0.000    -.8378006   -.5092815
                             1988  |  -.9775924   .0794303   -12.31   0.000    -1.133273   -.8219118
                             1994  |  -.8358436   .0852362    -9.81   0.000    -1.002904   -.6687837
                             1998  |  -1.171177   .0918104   -12.76   0.000    -1.351122    -.991232
                             2004  |  -1.224451    .095131   -12.87   0.000    -1.410904   -1.037997
                             2008  |  -1.507369   .1216842   -12.39   0.000    -1.745865   -1.268872
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.505395   .6237995                     -2.728019   -.2827701
                             /cut2 |   1.137216   .6231711                     -.0841767    2.358609
                             /cut3 |   2.614267   .6244728                      1.390323    3.838211
                             /cut4 |   5.130007   .6325434                      3.890245    6.369769
----------------------------------------------------------------------------------------------------

. est sto m1

. 
. ologit reve_1b i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r , r 

Iteration 0:   log pseudolikelihood = -9204.7672  
Iteration 1:   log pseudolikelihood = -8101.5966  
Iteration 2:   log pseudolikelihood = -8073.7021  
Iteration 3:   log pseudolikelihood = -8073.6594  
Iteration 4:   log pseudolikelihood = -8073.6594  

Ordered logistic regression                     Number of obs     =      6,378
                                                Wald chi2(92)     =    2018.62
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -8073.6594               Pseudo R2         =     0.1229

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1b |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.1502099   .0666871    -2.25   0.024    -.2809143   -.0195055
                     Man of Color  |  -.0567718    .103254    -0.55   0.582    -.2591459    .1456023
                   Woman of Color  |  -.5224028   .1693397    -3.08   0.002    -.8543025   -.1905032
                                   |
                     civil_service |
                              Yes  |  -.8010587   .0607996   -13.18   0.000    -.9202237   -.6818938
                      weekly_hours |   .0479222   .0033269    14.40   0.000     .0414016    .0544429
                               age |  -.0767768   .0231595    -3.32   0.001    -.1221687   -.0313849
                             age_2 |   .0007002   .0002276     3.08   0.002     .0002542    .0011462
                                   |
                               edu |
              High school or less  |   .2658405   .2268917     1.17   0.241     -.178859    .7105401
                     Some college  |   .1530398   .1191205     1.28   0.199    -.0804321    .3865117
                   Graduate study  |   .1476438   .0824394     1.79   0.073    -.0139344     .309222
                  Graduate degree  |   .0734268   .0687729     1.07   0.286    -.0613655    .2082192
                                   |
                years_employ_state |   .0056667   .0042638     1.33   0.184    -.0026902    .0140235
               years_employ_agency |  -.0282912   .0044624    -6.34   0.000    -.0370375    -.019545
             years_employ_position |  -.0066664    .005934    -1.12   0.261    -.0182968     .004964
                                   |
                              pid5 |
                       Republican  |   .3837354   .0851776     4.51   0.000     .2167903    .5506805
                  Lean Republican  |   .0228367   .1080157     0.21   0.833    -.1888702    .2345436
                  Lean Democratic  |  -.0635507   .0975554    -0.65   0.515    -.2547557    .1276544
                       Democratic  |   .3259516   .0797447     4.09   0.000      .169655    .4822483
                                   |
                       agency_size |
                           25-100  |  -.0445093   .0785051    -0.57   0.571    -.1983765     .109358
                          101-500  |   .1968848   .0895371     2.20   0.028     .0213954    .3723743
                        501-1,000  |   .3376189   .1193704     2.83   0.005     .1036573    .5715805
                      1,001-5,000  |   .6280194   .1251758     5.02   0.000     .3826794    .8733594
                       Over 5,000  |   1.022571   .1730498     5.91   0.000     .6833995    1.361742
                                   |
                 log_agency_budget |   .1899252   .0216562     8.77   0.000     .1474799    .2323705
                      inst6017_nom |   .0028871   .0031288     0.92   0.356    -.0032452    .0090195
                                   |
                          funcat13 |
                    Staff: Fiscal  |   1.405647   .1764997     7.96   0.000     1.059714     1.75158
                Staff: Non-Fiscal  |   .9466027    .184014     5.14   0.000     .5859419    1.307263
Income Security & Social Services  |  -.4537725   .1521941    -2.98   0.003    -.7520675   -.1554774
                        Education  |  -.4254235   .1625536    -2.62   0.009    -.7440227   -.1068244
                           Health  |  -.6096505   .1594823    -3.82   0.000    -.9222301   -.2970709
                Natural Resources  |  -.0851974   .1438454    -0.59   0.554    -.3671291    .1967344
             Environment & Energy  |   .0260771   .1494181     0.17   0.861    -.2667771    .3189312
             Economic Development  |   .7596595   .1528347     4.97   0.000     .4601089     1.05921
                 Criminal Justice  |   .0158167    .152794     0.10   0.918     -.283654    .3152875
                       Regulatory  |  -.6198936   .1436041    -4.32   0.000    -.9013524   -.3384348
                   Transportation  |  -.2217456   .1602336    -1.38   0.166    -.5357977    .0923064
                            Other  |   .1386793   .1519915     0.91   0.362    -.1592186    .4365771
                                   |
                             state |
                               AK  |  -.0763772   .2326042    -0.33   0.743     -.532273    .3795186
                               AZ  |  -.3752213   .2390634    -1.57   0.117     -.843777    .0933344
                               AR  |   .3394096   .2251537     1.51   0.132    -.1018836    .7807027
                               CA  |  -1.533002   .2558924    -5.99   0.000    -2.034542   -1.031462
                               CO  |  -.2716633   .2251548    -1.21   0.228    -.7129587     .169632
                               CT  |  -.8201582   .2658149    -3.09   0.002    -1.341146   -.2991707
                               DE  |   -.853052   .2246583    -3.80   0.000    -1.293374   -.4127299
                               FL  |  -1.320788   .2392821    -5.52   0.000    -1.789772   -.8518035
                               GA  |  -.8142959   .2564716    -3.17   0.001    -1.316971   -.3116208
                               HI  |  -1.396295    .267658    -5.22   0.000    -1.920895   -.8716948
                               ID  |    .726494   .2240838     3.24   0.001     .2872977     1.16569
                               IL  |  -.3944151   .2884722    -1.37   0.172    -.9598101      .17098
                               IN  |   .1277181   .2342384     0.55   0.586    -.3313807    .5868169
                               IA  |  -.3074279   .2208542    -1.39   0.164    -.7402941    .1254384
                               KS  |  -.5489781   .2269473    -2.42   0.016    -.9937866   -.1041696
                               KY  |  -.8118887   .2374382    -3.42   0.001    -1.277259   -.3465183
                               LA  |  -.3434393   .2497323    -1.38   0.169    -.8329057     .146027
                               ME  |   .1849485   .2444892     0.76   0.449    -.2942415    .6641386
                               MD  |  -.4369056   .2364424    -1.85   0.065    -.9003242     .026513
                               MA  |  -1.065537   .2666702    -4.00   0.000    -1.588201   -.5428731
                               MI  |  -.3496174   .2366052    -1.48   0.140     -.813355    .1141203
                               MN  |  -.9795967   .2251528    -4.35   0.000    -1.420888   -.5383054
                               MS  |  -.5658047   .2489902    -2.27   0.023    -1.053816   -.0777929
                               MO  |  -1.091504   .2314149    -4.72   0.000    -1.545069   -.6379394
                               MT  |   .1691514   .2047438     0.83   0.409     -.232139    .5704417
                               NE  |  -.2307015   .2256076    -1.02   0.307    -.6728842    .2114812
                               NV  |  -.2566648   .2268787    -1.13   0.258    -.7013389    .1880093
                               NH  |   .0673188   .2417316     0.28   0.781    -.4064663     .541104
                               NJ  |   -.835969   .2586301    -3.23   0.001    -1.342875   -.3290633
                               NM  |  -.2578871   .2347796    -1.10   0.272    -.7180467    .2022725
                               NY  |  -.2012437   .3048449    -0.66   0.509    -.7987287    .3962413
                               NC  |  -.9560659   .2161627    -4.42   0.000    -1.379737   -.5323947
                               ND  |   .2226899   .2054266     1.08   0.278    -.1799388    .6253187
                               OH  |  -.9561178   .2358251    -4.05   0.000    -1.418327    -.493909
                               OK  |  -.7989965   .2279037    -3.51   0.000     -1.24568   -.3523134
                               OR  |  -.3182658   .2248575    -1.42   0.157    -.7589785    .1224469
                               PA  |  -1.466266   .2569792    -5.71   0.000    -1.969936   -.9625957
                               RI  |   .3960384    .240397     1.65   0.099     -.075131    .8672078
                               SC  |   -.434628   .2319624    -1.87   0.061     -.889266      .02001
                               SD  |    .076803   .2277228     0.34   0.736    -.3695255    .5231314
                               TN  |  -1.131338   .2350654    -4.81   0.000    -1.592058   -.6706184
                               TX  |  -1.245401   .2258436    -5.51   0.000    -1.688046   -.8027554
                               UT  |  -.3692784     .20978    -1.76   0.078    -.7804396    .0418828
                               VT  |  -.0581917   .2315461    -0.25   0.802    -.5120136    .3956303
                               VA  |  -.7031821   .2705374    -2.60   0.009    -1.233426   -.1729386
                               WA  |  -.9891452   .2215726    -4.46   0.000     -1.42342   -.5548709
                               WV  |  -.4904082   .2651731    -1.85   0.064    -1.010138    .0293216
                               WI  |  -.5345467   .2221096    -2.41   0.016    -.9698736   -.0992198
                               WY  |   .1794183   .2104176     0.85   0.394    -.2329926    .5918291
                                   |
                              year |
                             1984  |   .0662276   .0898342     0.74   0.461    -.1098441    .2422993
                             1988  |   .1299014   .0872908     1.49   0.137    -.0411855    .3009882
                             1994  |    .022564   .0927151     0.24   0.808    -.1591542    .2042823
                             1998  |  -.1963388    .098583    -1.99   0.046    -.3895579   -.0031197
                             2004  |  -.2686975   .1042481    -2.58   0.010    -.4730201   -.0643749
                             2008  |  -.2719732   .1206671    -2.25   0.024    -.5084764     -.03547
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -3.539681   .6550552                     -4.823565   -2.255796
                             /cut2 |  -.5321222   .6469505                     -1.800122    .7358775
                             /cut3 |   .7528796   .6466974                     -.5146241    2.020383
                             /cut4 |   2.759331   .6485993                        1.4881    4.030562
----------------------------------------------------------------------------------------------------

. est sto m2

. 
. ologit reve_1c i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r , r 

Iteration 0:   log pseudolikelihood = -10351.868  
Iteration 1:   log pseudolikelihood = -9378.5499  
Iteration 2:   log pseudolikelihood =  -9360.604  
Iteration 3:   log pseudolikelihood = -9360.5601  
Iteration 4:   log pseudolikelihood = -9360.5601  

Ordered logistic regression                     Number of obs     =      7,543
                                                Wald chi2(93)     =    1799.99
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -9360.5601               Pseudo R2         =     0.0958

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1c |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.1532275   .0659598    -2.32   0.020    -.2825063   -.0239486
                     Man of Color  |  -.5317392   .0991337    -5.36   0.000    -.7260377   -.3374408
                   Woman of Color  |  -.6349348   .1816233    -3.50   0.000      -.99091   -.2789596
                                   |
                     civil_service |
                              Yes  |  -.4786386    .055548    -8.62   0.000    -.5875107   -.3697665
                      weekly_hours |   .0395543   .0029311    13.49   0.000     .0338095    .0452991
                               age |  -.0155138   .0219281    -0.71   0.479     -.058492    .0274645
                             age_2 |   6.43e-06   .0002187     0.03   0.977    -.0004222    .0004351
                                   |
                               edu |
              High school or less  |   .0429885   .2095777     0.21   0.837    -.3677762    .4537532
                     Some college  |  -.1672944   .1075566    -1.56   0.120    -.3781014    .0435126
                   Graduate study  |   .1129532   .0758331     1.49   0.136    -.0356769    .2615833
                  Graduate degree  |   .0497169    .060836     0.82   0.414    -.0695195    .1689534
                                   |
                years_employ_state |   .0049376    .003876     1.27   0.203    -.0026593    .0125345
               years_employ_agency |  -.0098846   .0041501    -2.38   0.017    -.0180186   -.0017505
             years_employ_position |   .0077178   .0053947     1.43   0.153    -.0028557    .0182912
                                   |
                              pid5 |
                       Republican  |   .2280009   .0778427     2.93   0.003      .075432    .3805697
                  Lean Republican  |  -.0335429   .0991719    -0.34   0.735    -.2279163    .1608306
                  Lean Democratic  |   -.002536   .0930573    -0.03   0.978     -.184925     .179853
                       Democratic  |   .1816716   .0728001     2.50   0.013      .038986    .3243572
                                   |
                       agency_size |
                           25-100  |   .2577081   .0703178     3.66   0.000     .1198877    .3955285
                          101-500  |   .4706283   .0811016     5.80   0.000      .311672    .6295846
                        501-1,000  |   .5575088   .1073675     5.19   0.000     .3470723    .7679452
                      1,001-5,000  |   .6310467   .1140187     5.53   0.000     .4075741    .8545194
                       Over 5,000  |   .8554307   .1566426     5.46   0.000     .5484169    1.162444
                                   |
                 log_agency_budget |   .1545551   .0190955     8.09   0.000     .1171286    .1919815
                      inst6017_nom |   .0036019   .0026201     1.37   0.169    -.0015333    .0087371
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.7217645   .1543915    -4.67   0.000    -1.024366   -.4191628
                Staff: Non-Fiscal  |  -1.344385   .1442132    -9.32   0.000    -1.627038   -1.061732
Income Security & Social Services  |  -1.544121   .1327481   -11.63   0.000    -1.804302   -1.283939
                        Education  |  -1.333907   .1431981    -9.32   0.000     -1.61457   -1.053244
                           Health  |  -1.444351    .138387   -10.44   0.000    -1.715585   -1.173118
                Natural Resources  |  -.9783398   .1251478    -7.82   0.000    -1.223625   -.7330546
             Environment & Energy  |  -1.157852   .1281523    -9.03   0.000    -1.409025   -.9066778
             Economic Development  |  -1.169661   .1311787    -8.92   0.000    -1.426767   -.9125557
                 Criminal Justice  |  -1.490325   .1327232   -11.23   0.000    -1.750458   -1.230192
                       Regulatory  |  -1.341997   .1238209   -10.84   0.000    -1.584681   -1.099312
                   Transportation  |   -.921331   .1483283    -6.21   0.000    -1.212049   -.6306128
                            Other  |  -1.484794   .1321397   -11.24   0.000    -1.743783   -1.225804
                                   |
                             state |
                               AK  |   .1844862   .2185489     0.84   0.399    -.2438617    .6128342
                               AZ  |   .0686257   .2388438     0.29   0.774    -.3994995    .5367509
                               AR  |   .5962324   .2429482     2.45   0.014     .1200627    1.072402
                               CA  |  -.0899827   .2443573    -0.37   0.713    -.5689141    .3889488
                               CO  |   .3909344   .2112609     1.85   0.064    -.0231294    .8049982
                               CT  |   .1792289   .2429228     0.74   0.461    -.2968911    .6553489
                               DE  |   .1713338   .2274411     0.75   0.451    -.2744427    .6171102
                               FL  |  -.5273958   .2248197    -2.35   0.019    -.9680344   -.0867573
                               GA  |   .3733606   .2261473     1.65   0.099      -.06988    .8166013
                               HI  |  -.4723271   .2657496    -1.78   0.076    -.9931867    .0485325
                               ID  |  -.0087548   .2270013    -0.04   0.969    -.4536692    .4361596
                               IL  |   .1443683   .2490528     0.58   0.562    -.3437662    .6325027
                               IN  |  -.2772225   .2239881    -1.24   0.216    -.7162311    .1617862
                               IA  |  -.0552067   .2152792    -0.26   0.798    -.4771462    .3667327
                               KS  |   .5429078   .2175227     2.50   0.013     .1165712    .9692445
                               KY  |   -.493915   .2355542    -2.10   0.036    -.9555926   -.0322373
                               LA  |   .6365047   .2605336     2.44   0.015     .1258682    1.147141
                               ME  |   .8528493   .2276178     3.75   0.000     .4067265    1.298972
                               MD  |   .2340007    .218611     1.07   0.284     -.194469    .6624704
                               MA  |    .473201   .2536004     1.87   0.062    -.0238466    .9702486
                               MI  |   .8221413   .2281193     3.60   0.000     .3750357    1.269247
                               MN  |   .3196358   .2101994     1.52   0.128    -.0923475     .731619
                               MS  |   .3302594    .238284     1.39   0.166    -.1367686    .7972874
                               MO  |   .3331271   .2166495     1.54   0.124    -.0914981    .7577523
                               MT  |  -.2830532   .2152178    -1.32   0.188    -.7048723    .1387659
                               NE  |  -.0741863    .218658    -0.34   0.734    -.5027482    .3543756
                               NV  |  -.7577281   .2102203    -3.60   0.000    -1.169752   -.3457039
                               NH  |   1.064797   .2139455     4.98   0.000     .6454716    1.484122
                               NJ  |  -.4378222   .2409223    -1.82   0.069    -.9100212    .0343767
                               NM  |  -.4457853   .2325061    -1.92   0.055    -.9014888    .0099182
                               NY  |  -.5236403    .270506    -1.94   0.053    -1.053822    .0065417
                               NC  |  -.1303479   .2013047    -0.65   0.517    -.5248978     .264202
                               ND  |  -.3949463   .2050011    -1.93   0.054    -.7967411    .0068485
                               OH  |  -.3798706   .2215315    -1.71   0.086    -.8140643    .0543231
                               OK  |    .767976    .230308     3.33   0.001     .3165807    1.219371
                               OR  |  -.2785938   .2128417    -1.31   0.191    -.6957559    .1385682
                               PA  |   .1065086   .2358795     0.45   0.652    -.3558068     .568824
                               RI  |  -.0517783   .2449748    -0.21   0.833    -.5319201    .4283636
                               SC  |   1.077082   .2380934     4.52   0.000     .6104275    1.543737
                               SD  |  -.8420329   .2224203    -3.79   0.000    -1.277969   -.4060971
                               TN  |   .0646205   .2385057     0.27   0.786    -.4028422    .5320831
                               TX  |  -.0094745   .2401865    -0.04   0.969    -.4802313    .4612823
                               UT  |  -.5591416   .2109727    -2.65   0.008    -.9726406   -.1456426
                               VT  |   .7496343   .2296456     3.26   0.001     .2995372    1.199731
                               VA  |  -.3137102   .2323159    -1.35   0.177    -.7690411    .1416206
                               WA  |  -.4032374   .2156546    -1.87   0.062    -.8259127    .0194378
                               WV  |  -.3648495   .2244198    -1.63   0.104    -.8047042    .0750051
                               WI  |   .2197584   .2066504     1.06   0.288     -.185269    .6247858
                               WY  |  -.7727914   .2178966    -3.55   0.000    -1.199861    -.345722
                                   |
                              year |
                             1978  |  -.5116036   .0906929    -5.64   0.000    -.6893584   -.3338489
                             1984  |   -.507846   .0878024    -5.78   0.000    -.6799355   -.3357565
                             1988  |  -.4688999   .0825201    -5.68   0.000    -.6306362   -.3071635
                             1994  |   -.466606     .08734    -5.34   0.000    -.6377892   -.2954228
                             1998  |  -.7226027   .0893663    -8.09   0.000    -.8977575    -.547448
                             2004  |  -.9583222   .0939958   -10.20   0.000    -1.142551   -.7740937
                             2008  |   -.933202   .1098137    -8.50   0.000    -1.148433   -.7179711
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -4.174863   .6145576                     -5.379374   -2.970353
                             /cut2 |  -.4940411   .6030479                     -1.675993     .687911
                             /cut3 |   .9883115   .6031423                     -.1938257    2.170449
                             /cut4 |   3.141685   .6040427                      1.957783    4.325587
----------------------------------------------------------------------------------------------------

. est sto m3

. 
. ologit reve_1d i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r , r 

Iteration 0:   log pseudolikelihood = -8728.3519  
Iteration 1:   log pseudolikelihood = -8200.6981  
Iteration 2:   log pseudolikelihood = -8194.7582  
Iteration 3:   log pseudolikelihood = -8194.7467  
Iteration 4:   log pseudolikelihood = -8194.7467  

Ordered logistic regression                     Number of obs     =      6,340
                                                Wald chi2(92)     =     999.27
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -8194.7467               Pseudo R2         =     0.0611

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.0915631   .0685134    -1.34   0.181    -.2258469    .0427207
                     Man of Color  |  -.2571474   .1004093    -2.56   0.010     -.453946   -.0603487
                   Woman of Color  |  -.6066361   .2065942    -2.94   0.003    -1.011553   -.2017189
                                   |
                     civil_service |
                              Yes  |  -.2674122   .0601311    -4.45   0.000    -.3852671   -.1495573
                      weekly_hours |   .0295276   .0031084     9.50   0.000     .0234353    .0356198
                               age |  -.0403184   .0252539    -1.60   0.110    -.0898151    .0091784
                             age_2 |   .0002548   .0002524     1.01   0.313    -.0002398    .0007494
                                   |
                               edu |
              High school or less  |   .0765339   .2636174     0.29   0.772    -.4401468    .5932146
                     Some college  |  -.0604091   .1194484    -0.51   0.613    -.2945238    .1737055
                   Graduate study  |   .1352846    .082029     1.65   0.099    -.0254892    .2960584
                  Graduate degree  |   .0574484   .0656242     0.88   0.381    -.0711726    .1860694
                                   |
                years_employ_state |   .0120718   .0040276     3.00   0.003      .004178    .0199657
               years_employ_agency |  -.0078704   .0043119    -1.83   0.068    -.0163215    .0005807
             years_employ_position |    .004455   .0056835     0.78   0.433    -.0066844    .0155945
                                   |
                              pid5 |
                       Republican  |   .0864186    .082324     1.05   0.294    -.0749334    .2477706
                  Lean Republican  |   .0044505   .1093365     0.04   0.968    -.2098452    .2187461
                  Lean Democratic  |  -.0091306   .1026936    -0.09   0.929    -.2104064    .1921451
                       Democratic  |   .0612516    .076418     0.80   0.423    -.0885249    .2110281
                                   |
                       agency_size |
                           25-100  |   .0577822   .0742731     0.78   0.437    -.0877903    .2033547
                          101-500  |   .0949199   .0847446     1.12   0.263    -.0711766    .2610163
                        501-1,000  |   .1025891   .1174273     0.87   0.382    -.1275642    .3327423
                      1,001-5,000  |  -.0089695   .1225841    -0.07   0.942    -.2492299    .2312908
                       Over 5,000  |   .2036781    .166484     1.22   0.221    -.1226246    .5299808
                                   |
                 log_agency_budget |   .0999747   .0206675     4.84   0.000     .0594671    .1404823
                      inst6017_nom |   .0060982   .0029472     2.07   0.039     .0003217    .0118747
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.1229972   .1637844    -0.75   0.453    -.4440087    .1980144
                Staff: Non-Fiscal  |  -.8768568   .1644321    -5.33   0.000    -1.199138   -.5545758
Income Security & Social Services  |  -.9503731   .1509034    -6.30   0.000    -1.246138    -.654608
                        Education  |  -.6935631   .1615647    -4.29   0.000    -1.010224    -.376902
                           Health  |  -.9182932   .1576484    -5.82   0.000    -1.227278    -.609308
                Natural Resources  |  -.9120763   .1430177    -6.38   0.000    -1.192386   -.6317669
             Environment & Energy  |  -1.032433   .1439321    -7.17   0.000    -1.314535   -.7503316
             Economic Development  |  -1.134385    .147684    -7.68   0.000     -1.42384   -.8449294
                 Criminal Justice  |  -.9563278   .1512715    -6.32   0.000    -1.252815    -.659841
                       Regulatory  |  -1.162944   .1406683    -8.27   0.000    -1.438649   -.8872391
                   Transportation  |  -.8374815   .1672608    -5.01   0.000    -1.165307   -.5096564
                            Other  |  -.9052627   .1495118    -6.05   0.000      -1.1983    -.612225
                                   |
                             state |
                               AK  |   1.399893   .2527265     5.54   0.000     .9045582    1.895228
                               AZ  |   .9238635   .2647702     3.49   0.000     .4049235    1.442804
                               AR  |   .7222201   .2597652     2.78   0.005     .2130896    1.231351
                               CA  |   1.040541   .2968631     3.51   0.000     .4586997    1.622382
                               CO  |   .7062144   .2520423     2.80   0.005     .2122207    1.200208
                               CT  |     .54922   .2832048     1.94   0.052    -.0058512    1.104291
                               DE  |   .0967001   .2752153     0.35   0.725    -.4427119    .6361121
                               FL  |    .917924   .2599173     3.53   0.000     .4084954    1.427353
                               GA  |   .4995448   .2725782     1.83   0.067    -.0346986    1.033788
                               HI  |   -.098179   .2951121    -0.33   0.739    -.6765881    .4802301
                               ID  |   .5452425   .2527906     2.16   0.031      .049782    1.040703
                               IL  |   .5357001   .2844619     1.88   0.060     -.021835    1.093235
                               IN  |   .1926003   .2668031     0.72   0.470    -.3303242    .7155247
                               IA  |   .4623393   .2506624     1.84   0.065      -.02895    .9536285
                               KS  |   1.192527    .257752     4.63   0.000     .6873425    1.697712
                               KY  |   .6270707   .2615218     2.40   0.016     .1144974    1.139644
                               LA  |   .8133197   .2889778     2.81   0.005     .2469336    1.379706
                               ME  |   .8874817   .2850533     3.11   0.002     .3287874    1.446176
                               MD  |   .8027602   .2583373     3.11   0.002     .2964284    1.309092
                               MA  |   .8799829   .2921223     3.01   0.003     .3074338    1.452532
                               MI  |   1.697745   .2692553     6.31   0.000     1.170015    2.225476
                               MN  |   1.185779    .249503     4.75   0.000     .6967623    1.674796
                               MS  |   .4389355   .2610983     1.68   0.093    -.0728077    .9506787
                               MO  |   .7516882   .2590888     2.90   0.004     .2438835    1.259493
                               MT  |   .4021156   .2465757     1.63   0.103    -.0811638    .8853951
                               NE  |   .9359898   .2584906     3.62   0.000     .4293575    1.442622
                               NV  |   .4210234   .2464239     1.71   0.088    -.0619585    .9040053
                               NH  |    .861979   .2763309     3.12   0.002     .3203805    1.403578
                               NJ  |   .3240292   .2653246     1.22   0.222    -.1959976    .8440559
                               NM  |    .450611   .2702053     1.67   0.095    -.0789816    .9802036
                               NY  |   .3916939   .3532072     1.11   0.267    -.3005795    1.083967
                               NC  |   .3156418   .2418451     1.31   0.192    -.1583658    .7896494
                               ND  |  -.6404053   .2569048    -2.49   0.013    -1.143929   -.1368812
                               OH  |   .5187461   .2821676     1.84   0.066    -.0342923    1.071784
                               OK  |   1.100864   .2567021     4.29   0.000      .597737    1.603991
                               OR  |   .6240373   .2571202     2.43   0.015     .1200909    1.127984
                               PA  |   1.029567   .2757739     3.73   0.000     .4890604    1.570074
                               RI  |  -.2562584   .2859077    -0.90   0.370    -.8166271    .3041104
                               SC  |   1.400709   .2775545     5.05   0.000     .8567119    1.944705
                               SD  |  -.2997918   .2582692    -1.16   0.246    -.8059901    .2064065
                               TN  |   .5386902   .2678191     2.01   0.044     .0137745    1.063606
                               TX  |   1.567741   .2655896     5.90   0.000     1.047195    2.088287
                               UT  |   .5426185   .2399215     2.26   0.024     .0723809    1.012856
                               VT  |   .2893295   .2762285     1.05   0.295    -.2520685    .8307275
                               VA  |   .3164445   .2611018     1.21   0.226    -.1953056    .8281945
                               WA  |   .6177409   .2398288     2.58   0.010     .1476851    1.087797
                               WV  |   .1170794   .2607521     0.45   0.653    -.3939852    .6281441
                               WI  |   1.243647   .2552009     4.87   0.000     .7434623    1.743831
                               WY  |  -.2981704   .2535781    -1.18   0.240    -.7951743    .1988335
                                   |
                              year |
                             1984  |  -.0881298   .0899369    -0.98   0.327     -.264403    .0881433
                             1988  |    .154664   .0867667     1.78   0.075    -.0153957    .3247236
                             1994  |   .2173252   .0923942     2.35   0.019     .0362359    .3984145
                             1998  |  -.0626998   .0978743    -0.64   0.522    -.2545298    .1291302
                             2004  |  -.4073416   .1006214    -4.05   0.000    -.6045558   -.2101273
                             2008  |  -.1814891   .1131612    -1.60   0.109    -.4032808    .0403027
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -3.267728   .6941545                     -4.628246    -1.90721
                             /cut2 |  -.2093042   .6874764                     -1.556733    1.138125
                             /cut3 |   1.214853   .6876623                       -.13294    2.562647
                             /cut4 |   3.379304   .6887325                      2.029413    4.729195
----------------------------------------------------------------------------------------------------

. est sto m4

. 
.  esttab m1 m2 m3 m4 using Table_2.rtf ,starlevels(+ 0.10 * 0.05 ** 0.01) cells(b(star fmt(3)) se(par fmt(3)
> )) ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Gov." "Gov. Staff" "Legis." "Legis. Staff" )
(output written to Table_2.rtf)

. 
. 
. ***** CODE USED TO PRODUCE TABLE 3 ******
. est restore m1
(results m1 are active now)

. margins, dydx(3.intersection)

Average marginal effects                        Number of obs     =      7,515
Model VCE    : Robust

dy/dx w.r.t. : 3.intersection
1._predict   : Pr(reve_1a==1), predict(pr outcome(1))
2._predict   : Pr(reve_1a==2), predict(pr outcome(2))
3._predict   : Pr(reve_1a==3), predict(pr outcome(3))
4._predict   : Pr(reve_1a==4), predict(pr outcome(4))
5._predict   : Pr(reve_1a==5), predict(pr outcome(5))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
0.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |   .0660135   .0232189     2.84   0.004     .0205052    .1115218
             2  |   .0234142   .0042921     5.46   0.000     .0150018    .0318267
             3  |  -.0342882   .0117702    -2.91   0.004    -.0573573   -.0112191
             4  |  -.0454374   .0131181    -3.46   0.001    -.0711483   -.0197265
             5  |  -.0097022   .0025627    -3.79   0.000    -.0147249   -.0046794
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. 
. est restore m2
(results m2 are active now)

. margins, dydx(3.intersection)

Average marginal effects                        Number of obs     =      6,378
Model VCE    : Robust

dy/dx w.r.t. : 3.intersection
1._predict   : Pr(reve_1b==1), predict(pr outcome(1))
2._predict   : Pr(reve_1b==2), predict(pr outcome(2))
3._predict   : Pr(reve_1b==3), predict(pr outcome(3))
4._predict   : Pr(reve_1b==4), predict(pr outcome(4))
5._predict   : Pr(reve_1b==5), predict(pr outcome(5))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
0.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |   .0149243   .0059794     2.50   0.013     .0032048    .0266437
             2  |   .0729168   .0242856     3.00   0.003      .025318    .1205157
             3  |   .0116467   .0017338     6.72   0.000     .0082485    .0150449
             4  |  -.0450552    .016199    -2.78   0.005    -.0768046   -.0133057
             5  |  -.0544326     .01547    -3.52   0.000    -.0847533   -.0241119
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. 
. est restore m3
(results m3 are active now)

. margins, dydx(3.intersection)

Average marginal effects                        Number of obs     =      7,543
Model VCE    : Robust

dy/dx w.r.t. : 3.intersection
1._predict   : Pr(reve_1c==1), predict(pr outcome(1))
2._predict   : Pr(reve_1c==2), predict(pr outcome(2))
3._predict   : Pr(reve_1c==3), predict(pr outcome(3))
4._predict   : Pr(reve_1c==4), predict(pr outcome(4))
5._predict   : Pr(reve_1c==5), predict(pr outcome(5))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
0.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |   .0097756   .0037619     2.60   0.009     .0024024    .0171488
             2  |   .1057739    .031833     3.32   0.001     .0433823    .1681655
             3  |   .0084935   .0025096     3.38   0.001     .0035747    .0134123
             4  |  -.0771653    .022696    -3.40   0.001    -.1216486   -.0326819
             5  |  -.0468777    .010762    -4.36   0.000    -.0679708   -.0257845
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. 
. est restore m4
(results m4 are active now)

. margins, dydx(3.intersection)

Average marginal effects                        Number of obs     =      6,340
Model VCE    : Robust

dy/dx w.r.t. : 3.intersection
1._predict   : Pr(reve_1d==1), predict(pr outcome(1))
2._predict   : Pr(reve_1d==2), predict(pr outcome(2))
3._predict   : Pr(reve_1d==3), predict(pr outcome(3))
4._predict   : Pr(reve_1d==4), predict(pr outcome(4))
5._predict   : Pr(reve_1d==5), predict(pr outcome(5))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
0.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |    .018064   .0079872     2.26   0.024     .0024093    .0337187
             2  |   .1050176   .0364494     2.88   0.004     .0335781    .1764571
             3  |  -.0030811   .0070609    -0.44   0.663    -.0169202     .010758
             4  |  -.0844312   .0279762    -3.02   0.003    -.1392635   -.0295988
             5  |  -.0355694   .0095888    -3.71   0.000     -.054363   -.0167758
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. 
. **** RESULTS EXPORTED AND FORMATTED IN EXCEL ****
. 
. **** CODE USED TO PRODUCE TABLE 3 ****
. 
. ologit d_15a i.intersection i.reve_1a i.reve_1b i.civil_service weekly_hours age age_2 b3.edu years_employ_
> state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fun
> cat13 i.state i.year , r 

Iteration 0:   log pseudolikelihood = -6426.3351  
Iteration 1:   log pseudolikelihood = -5816.9392  
Iteration 2:   log pseudolikelihood = -5786.9108  
Iteration 3:   log pseudolikelihood = -5786.6431  
Iteration 4:   log pseudolikelihood =  -5786.643  

Ordered logistic regression                     Number of obs     =      6,224
                                                Wald chi2(100)    =    1116.77
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -5786.643               Pseudo R2         =     0.0995

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_15a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.1242675   .0782702    -1.59   0.112    -.2776743    .0291393
                     Man of Color  |   .3003436    .118261     2.54   0.011     .0685562     .532131
                   Woman of Color  |   .5525573   .2348854     2.35   0.019     .0921905    1.012924
                                   |
                           reve_1a |
                Less than Monthly  |    .242045   .0806949     3.00   0.003      .083886     .400204
                          Monthly  |   .2699382   .1042403     2.59   0.010     .0656309    .4742454
                           Weekly  |   .5819831   .1370869     4.25   0.000     .3132976    .8506686
                            Daily  |   1.462612   .3665643     3.99   0.000     .7441588    2.181064
                                   |
                           reve_1b |
                Less than Monthly  |   .3770689    .188102     2.00   0.045     .0083958     .745742
                          Monthly  |   .5959252    .193513     3.08   0.002     .2166466    .9752038
                           Weekly  |   1.053024   .1993155     5.28   0.000     .6623727    1.443675
                            Daily  |   1.584073   .2195217     7.22   0.000     1.153818    2.014327
                                   |
                     civil_service |
                              Yes  |   .1646428   .0693698     2.37   0.018     .0286806    .3006051
                      weekly_hours |  -.0057133   .0035917    -1.59   0.112    -.0127529    .0013264
                               age |   .0131835   .0253898     0.52   0.604    -.0365797    .0629466
                             age_2 |  -.0002081    .000251    -0.83   0.407       -.0007    .0002838
                                   |
                               edu |
              High school or less  |  -.0076404   .2623902    -0.03   0.977    -.5219157    .5066349
                     Some college  |   -.230757   .1360871    -1.70   0.090    -.4974828    .0359687
                   Graduate study  |   .1571962   .0967201     1.63   0.104    -.0323718    .3467642
                  Graduate degree  |   -.115084   .0762292    -1.51   0.131    -.2644904    .0343225
                                   |
                years_employ_state |  -.0007676   .0047777    -0.16   0.872    -.0101318    .0085966
               years_employ_agency |  -.0030764   .0050216    -0.61   0.540    -.0129186    .0067658
             years_employ_position |  -.0192047   .0062911    -3.05   0.002     -.031535   -.0068743
                                   |
                              pid5 |
                       Republican  |  -.0104676    .093611    -0.11   0.911    -.1939418    .1730066
                  Lean Republican  |  -.0427336   .1203977    -0.35   0.723    -.2787087    .1932416
                  Lean Democratic  |  -.0735414   .1111346    -0.66   0.508    -.2913613    .1442784
                       Democratic  |  -.0795953   .0860246    -0.93   0.355    -.2482004    .0890098
                                   |
                       agency_size |
                           25-100  |   .0650051   .0863345     0.75   0.451    -.1042074    .2342175
                          101-500  |  -.0988579   .0975911    -1.01   0.311    -.2901329    .0924171
                        501-1,000  |  -.0928467   .1275701    -0.73   0.467    -.3428794    .1571861
                      1,001-5,000  |   -.202682   .1354394    -1.50   0.135    -.4681383    .0627744
                       Over 5,000  |  -.1535326   .1855774    -0.83   0.408    -.5172576    .2101925
                                   |
                 log_agency_budget |   .0477385    .022767     2.10   0.036     .0031161     .092361
                      inst6017_nom |  -.0016483   .0033451    -0.49   0.622    -.0082045     .004908
                                   |
                          funcat13 |
                    Staff: Fiscal  |   2.550807   .1867588    13.66   0.000     2.184766    2.916847
                Staff: Non-Fiscal  |   2.885916   .1862319    15.50   0.000     2.520909    3.250924
Income Security & Social Services  |   1.951379   .1545497    12.63   0.000     1.648467     2.25429
                        Education  |   1.757852   .1651857    10.64   0.000     1.434094     2.08161
                           Health  |   1.926734   .1621126    11.89   0.000        1.609    2.244469
                Natural Resources  |    1.83691   .1437309    12.78   0.000     1.555202    2.118617
             Environment & Energy  |   2.455734   .1555992    15.78   0.000     2.150765    2.760702
             Economic Development  |    2.17803    .163912    13.29   0.000     1.856768    2.499292
                 Criminal Justice  |   2.211354   .1560847    14.17   0.000     1.905433    2.517274
                       Regulatory  |   1.790367   .1460524    12.26   0.000     1.504109    2.076624
                   Transportation  |   2.335863   .1770497    13.19   0.000     1.988852    2.682874
                            Other  |   1.875953   .1565879    11.98   0.000     1.569046    2.182859
                                   |
                             state |
                               AK  |   1.118635   .2508777     4.46   0.000     .6269236    1.610346
                               AZ  |   .5056424   .2736559     1.85   0.065    -.0307133    1.041998
                               AR  |   .9488965   .2830409     3.35   0.001     .3941465    1.503647
                               CA  |   1.438984   .3058684     4.70   0.000      .839493    2.038475
                               CO  |    .240694   .2485303     0.97   0.333    -.2464164    .7278044
                               CT  |   1.158903   .3225803     3.59   0.000     .5266571    1.791149
                               DE  |   1.287364   .2522201     5.10   0.000     .7930222    1.781707
                               FL  |   .7672606   .2768492     2.77   0.006     .2246461    1.309875
                               GA  |   .9716983   .2603481     3.73   0.000     .4614253    1.481971
                               HI  |   1.161814   .2828206     4.11   0.000     .6074962    1.716132
                               ID  |   .5409002   .2517718     2.15   0.032     .0474365    1.034364
                               IL  |   1.140007   .3117587     3.66   0.000     .5289712    1.751043
                               IN  |   1.034193   .2701899     3.83   0.000     .5046305    1.563756
                               IA  |   .7512684    .254304     2.95   0.003     .2528418    1.249695
                               KS  |   1.132718    .275435     4.11   0.000     .5928758    1.672561
                               KY  |   1.133183   .2702791     4.19   0.000     .6034455     1.66292
                               LA  |   .7583673    .300506     2.52   0.012     .1693863    1.347348
                               ME  |   1.076142   .2790176     3.86   0.000     .5292778    1.623007
                               MD  |    1.28201   .2642626     4.85   0.000     .7640653    1.799956
                               MA  |   .7257357   .2733615     2.65   0.008     .1899571    1.261514
                               MI  |   1.238845   .2544387     4.87   0.000     .7401546    1.737536
                               MN  |   .9016696   .2370125     3.80   0.000     .4371336    1.366206
                               MS  |  -.3741053   .2529231    -1.48   0.139    -.8698255    .1216149
                               MO  |   .8476494   .2561112     3.31   0.001     .3456807    1.349618
                               MT  |   .6210894   .2450149     2.53   0.011     .1408691     1.10131
                               NE  |   .8859937   .2526356     3.51   0.000     .3908371     1.38115
                               NV  |   1.015144   .2625029     3.87   0.000     .5006472     1.52964
                               NH  |   .9847659   .2759728     3.57   0.000     .4438692    1.525663
                               NJ  |   1.618078   .2865569     5.65   0.000     1.056437    2.179719
                               NM  |   1.102043   .2774919     3.97   0.000     .5581689    1.645917
                               NY  |   1.696496   .3994221     4.25   0.000     .9136435    2.479349
                               NC  |   .7415078   .2341999     3.17   0.002     .2824845    1.200531
                               ND  |   .5759193   .2398648     2.40   0.016     .1057929    1.046046
                               OH  |   .9131874   .2665372     3.43   0.001     .3907841    1.435591
                               OK  |   .2570393   .2440745     1.05   0.292    -.2213379    .7354166
                               OR  |   .6114015   .2458722     2.49   0.013     .1295007    1.093302
                               PA  |   1.204994   .2588476     4.66   0.000      .697662    1.712326
                               RI  |   .9878919   .2909942     3.39   0.001     .4175537     1.55823
                               SC  |  -.0725063   .2568405    -0.28   0.778    -.5759045    .4308919
                               SD  |   1.077479   .2674244     4.03   0.000     .5533365    1.601621
                               TN  |   .9778272   .2593315     3.77   0.000     .4695467    1.486108
                               TX  |  -.3600298   .2546436    -1.41   0.157    -.8591221    .1390626
                               UT  |   .9676516   .2363207     4.09   0.000     .5044715    1.430832
                               VT  |   1.092281   .2756319     3.96   0.000     .5520523    1.632509
                               VA  |   1.171459   .2810788     4.17   0.000     .6205547    1.722363
                               WA  |   .8721144   .2682658     3.25   0.001     .3463232    1.397906
                               WV  |   .5587808   .2679866     2.09   0.037     .0335368    1.084025
                               WI  |   1.576222     .26331     5.99   0.000     1.060144      2.0923
                               WY  |   .5428254   .2466473     2.20   0.028     .0594055    1.026245
                                   |
                              year |
                             1984  |   .1462641   .1015257     1.44   0.150    -.0527227    .3452508
                             1988  |    .098596   .0965697     1.02   0.307    -.0906772    .2878693
                             1994  |    .450507   .1047791     4.30   0.000     .2451437    .6558703
                             1998  |   .6407183   .1119514     5.72   0.000     .4212975    .8601391
                             2004  |   .2844813   .1144668     2.49   0.013     .0601304    .5088322
                             2008  |   .5527944    .124162     4.45   0.000     .3094414    .7961474
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -.0179737   .7150855                     -1.419515    1.383568
                             /cut2 |   1.955136   .7171092                      .5496276    3.360644
                             /cut3 |   3.549956   .7185355                      2.141652    4.958259
----------------------------------------------------------------------------------------------------

. est sto m5

. 
. ologit d_16a i.intersection i.reve_1c  i.reve_1d i.civil_service weekly_hours age age_2 b3.edu years_employ
> _state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fu
> ncat13 i.state i.year , r 

Iteration 0:   log pseudolikelihood = -6643.7859  
Iteration 1:   log pseudolikelihood = -6425.2357  
Iteration 2:   log pseudolikelihood = -6424.0205  
Iteration 3:   log pseudolikelihood =   -6424.02  

Ordered logistic regression                     Number of obs     =      6,200
                                                Wald chi2(100)    =     418.80
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =   -6424.02               Pseudo R2         =     0.0331

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_16a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |   .0369801   .0722524     0.51   0.609     -.104632    .1785922
                     Man of Color  |   .2540965   .1112051     2.28   0.022     .0361385    .4720545
                   Woman of Color  |   .4311526   .2121116     2.03   0.042     .0154216    .8468837
                                   |
                           reve_1c |
                Less than Monthly  |  -.4533227   .2713594    -1.67   0.095    -.9851773     .078532
                          Monthly  |  -.3840042   .2735845    -1.40   0.160    -.9202199    .1522115
                           Weekly  |  -.2484308   .2775938    -0.89   0.371    -.7925048    .2956431
                            Daily  |  -.3010773   .2980155    -1.01   0.312     -.885177    .2830223
                                   |
                           reve_1d |
                Less than Monthly  |   .5725446    .212241     2.70   0.007     .1565599    .9885294
                          Monthly  |   .7406869   .2122158     3.49   0.000     .3247515    1.156622
                           Weekly  |   .9205621   .2149619     4.28   0.000     .4992446     1.34188
                            Daily  |   1.300182   .2414965     5.38   0.000      .826858    1.773507
                                   |
                     civil_service |
                              Yes  |   .0752613   .0645032     1.17   0.243    -.0511627    .2016852
                      weekly_hours |  -.0017046   .0032229    -0.53   0.597    -.0080214    .0046123
                               age |   .0471632   .0234172     2.01   0.044     .0012664    .0930601
                             age_2 |  -.0004258   .0002325    -1.83   0.067    -.0008816    .0000299
                                   |
                               edu |
              High school or less  |    .037846   .2778249     0.14   0.892    -.5066808    .5823729
                     Some college  |  -.1283292   .1248928    -1.03   0.304    -.3731146    .1164563
                   Graduate study  |   .0548737   .0871404     0.63   0.529    -.1159184    .2256658
                  Graduate degree  |   -.072935     .07098    -1.03   0.304    -.2120532    .0661832
                                   |
                years_employ_state |   .0083404   .0044529     1.87   0.061    -.0003871     .017068
               years_employ_agency |  -.0100326   .0046731    -2.15   0.032    -.0191917   -.0008734
             years_employ_position |  -.0089602   .0061255    -1.46   0.144    -.0209659    .0030455
                                   |
                              pid5 |
                       Republican  |   -.153614    .086783    -1.77   0.077    -.3237055    .0164776
                  Lean Republican  |   .0157165   .1137018     0.14   0.890    -.2071349    .2385678
                  Lean Democratic  |   .0319403   .1077806     0.30   0.767    -.1793058    .2431865
                       Democratic  |  -.0824199   .0817671    -1.01   0.313    -.2426804    .0778406
                                   |
                       agency_size |
                           25-100  |   .1047572   .0813467     1.29   0.198    -.0546794    .2641939
                          101-500  |    .105171   .0930164     1.13   0.258    -.0771378    .2874798
                        501-1,000  |  -.0853345   .1210675    -0.70   0.481    -.3226225    .1519534
                      1,001-5,000  |   -.170412    .128199    -1.33   0.184    -.4216774    .0808533
                       Over 5,000  |  -.1603723   .1739652    -0.92   0.357    -.5013379    .1805933
                                   |
                 log_agency_budget |   .0351698   .0213656     1.65   0.100     -.006706    .0770457
                      inst6017_nom |   .0080557    .003169     2.54   0.011     .0018447    .0142667
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.0780437   .1716258    -0.45   0.649    -.4144241    .2583367
                Staff: Non-Fiscal  |   .0178142   .1742054     0.10   0.919    -.3236222    .3592506
Income Security & Social Services  |  -.1699223   .1620991    -1.05   0.295    -.4876306    .1477861
                        Education  |   .0927977   .1819139     0.51   0.610    -.2637471    .4493424
                           Health  |   .0115461   .1731204     0.07   0.947    -.3277637    .3508559
                Natural Resources  |  -.2611242   .1525907    -1.71   0.087    -.5601965    .0379482
             Environment & Energy  |   .1012103   .1609382     0.63   0.529    -.2142229    .4166434
             Economic Development  |  -.3359153   .1625708    -2.07   0.039    -.6545482   -.0172824
                 Criminal Justice  |   .2113475   .1648383     1.28   0.200    -.1117296    .5344246
                       Regulatory  |     .02643   .1545177     0.17   0.864    -.2764191     .329279
                   Transportation  |   .0761095   .1718228     0.44   0.658     -.260657     .412876
                            Other  |  -.4628175    .161796    -2.86   0.004    -.7799318   -.1457032
                                   |
                             state |
                               AK  |     .76302   .2429988     3.14   0.002      .286751    1.239289
                               AZ  |   .8282129   .2603889     3.18   0.001     .3178601    1.338566
                               AR  |   .6244279   .2489101     2.51   0.012     .1365731    1.112283
                               CA  |   .8294245    .271129     3.06   0.002     .2980215    1.360827
                               CO  |    1.01677   .2540534     4.00   0.000     .5188349    1.514706
                               CT  |   .8345932   .2912368     2.87   0.004     .2637796    1.405407
                               DE  |   .9237991    .248665     3.72   0.000     .4364247    1.411173
                               FL  |   1.171684   .2610671     4.49   0.000     .6600024    1.683366
                               GA  |   .5026266   .2692115     1.87   0.062    -.0250181    1.030271
                               HI  |   .5385426   .2685374     2.01   0.045      .012219    1.064866
                               ID  |   .7519688   .2492582     3.02   0.003     .2634317    1.240506
                               IL  |   .4156331    .269652     1.54   0.123    -.1128751    .9441413
                               IN  |   .5850284   .2436898     2.40   0.016     .1074052    1.062652
                               IA  |   .9377369   .2408795     3.89   0.000     .4656218    1.409852
                               KS  |   1.237952   .2578128     4.80   0.000      .732648    1.743256
                               KY  |   .5273884    .245142     2.15   0.031     .0469189    1.007858
                               LA  |   .1453688   .2645546     0.55   0.583    -.3731487    .6638863
                               ME  |   1.153925   .2723147     4.24   0.000     .6201977    1.687652
                               MD  |   .4841354   .2535855     1.91   0.056     -.012883    .9811538
                               MA  |  -.0304925   .2562998    -0.12   0.905    -.5328309    .4718459
                               MI  |   .1584447   .2467925     0.64   0.521    -.3252598    .6421492
                               MN  |   1.195355   .2428238     4.92   0.000     .7194294    1.671281
                               MS  |   .9439424   .2554439     3.70   0.000     .4432815    1.444603
                               MO  |   .4462451   .2464868     1.81   0.070    -.0368602    .9293503
                               MT  |   .7373892   .2322118     3.18   0.001     .2822624    1.192516
                               NE  |   1.028459   .2546141     4.04   0.000     .5294243    1.527493
                               NV  |   .9976947   .2463363     4.05   0.000     .5148844    1.480505
                               NH  |   1.320917   .2599434     5.08   0.000     .8114375    1.830397
                               NJ  |   .7615457   .2593379     2.94   0.003     .2532529    1.269839
                               NM  |   .7259687   .2624718     2.77   0.006     .2115336    1.240404
                               NY  |   .5955434   .2835684     2.10   0.036     .0397595    1.151327
                               NC  |   .8279354   .2361117     3.51   0.000     .3651649    1.290706
                               ND  |   .8598149   .2404284     3.58   0.000     .3885839    1.331046
                               OH  |   .4276222   .2512876     1.70   0.089    -.0648924    .9201368
                               OK  |    1.25129   .2564651     4.88   0.000     .7486277    1.753952
                               OR  |   1.353209   .2503429     5.41   0.000     .8625462    1.843872
                               PA  |   .0842203   .2452511     0.34   0.731     -.396463    .5649036
                               RI  |   .4250767    .270156     1.57   0.116    -.1044194    .9545728
                               SC  |   .7896953   .2723867     2.90   0.004     .2558272    1.323563
                               SD  |   .4696611   .2422687     1.94   0.053    -.0051769    .9444991
                               TN  |   .2094934   .2535582     0.83   0.409    -.2874715    .7064583
                               TX  |   1.281149   .2742229     4.67   0.000     .7436819    1.818616
                               UT  |   1.152184   .2461871     4.68   0.000     .6696666    1.634702
                               VT  |   .7151062   .2467205     2.90   0.004     .2315428    1.198669
                               VA  |   .9988064   .2666911     3.75   0.000     .4761014    1.521511
                               WA  |   .8397862   .2607011     3.22   0.001     .3288214    1.350751
                               WV  |   .6028848   .2593412     2.32   0.020     .0945854    1.111184
                               WI  |   .7353899   .2442472     3.01   0.003     .2566742    1.214106
                               WY  |    .773118   .2492118     3.10   0.002     .2846719    1.261564
                                   |
                              year |
                             1984  |   .0414154   .0934189     0.44   0.658    -.1416822    .2245131
                             1988  |   .0053983   .0882855     0.06   0.951     -.167638    .1784347
                             1994  |   .1720171   .0962954     1.79   0.074    -.0167185    .3607526
                             1998  |   .3386069   .1013993     3.34   0.001      .139868    .5373458
                             2004  |    .074874   .1064452     0.70   0.482    -.1337547    .2835028
                             2008  |   .2286511   .1153025     1.98   0.047     .0026625    .4546398
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.179245    .720337                      -2.59108    .2325897
                             /cut2 |   1.088142   .7159694                     -.3151323    2.491416
                             /cut3 |    2.95614   .7171386                      1.550575    4.361706
----------------------------------------------------------------------------------------------------

. est sto m6

. 
.  
. ologit d_20a i.intersection i.reve_1a i.reve_1b  i.civil_service weekly_hours age age_2 b3.edu years_employ
> _state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fu
> ncat13 i.state i.year , r  

Iteration 0:   log pseudolikelihood = -7996.7677  
Iteration 1:   log pseudolikelihood = -7507.2228  
Iteration 2:   log pseudolikelihood = -7501.4617  
Iteration 3:   log pseudolikelihood = -7501.4509  
Iteration 4:   log pseudolikelihood = -7501.4509  

Ordered logistic regression                     Number of obs     =      6,175
                                                Wald chi2(100)    =     907.54
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -7501.4509               Pseudo R2         =     0.0619

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_20a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |   -.223584   .0692901    -3.23   0.001    -.3593901   -.0877779
                     Man of Color  |   .2070339   .1037175     2.00   0.046     .0037512    .4103165
                   Woman of Color  |    .498217   .1951696     2.55   0.011     .1156917    .8807423
                                   |
                           reve_1a |
                Less than Monthly  |   .2163756   .0777145     2.78   0.005      .064058    .3686931
                          Monthly  |   .2735757   .0981762     2.79   0.005     .0811539    .4659974
                           Weekly  |   .4128912    .118585     3.48   0.000     .1804689    .6453134
                            Daily  |    .620476   .2192635     2.83   0.005     .1907274    1.050225
                                   |
                           reve_1b |
                Less than Monthly  |    .237213   .1973241     1.20   0.229    -.1495352    .6239611
                          Monthly  |   .4180031   .2020811     2.07   0.039     .0219314    .8140747
                           Weekly  |   .6419187   .2049054     3.13   0.002     .2403115    1.043526
                            Daily  |   .8702175   .2162423     4.02   0.000     .4463904    1.294045
                                   |
                     civil_service |
                              Yes  |   .2147597   .0638385     3.36   0.001     .0896386    .3398809
                      weekly_hours |  -.0013704   .0031891    -0.43   0.667    -.0076209    .0048802
                               age |  -.0225404   .0233922    -0.96   0.335    -.0683882    .0233074
                             age_2 |   .0001661   .0002316     0.72   0.473    -.0002878    .0006201
                                   |
                               edu |
              High school or less  |   .3539448   .2626816     1.35   0.178    -.1609017    .8687914
                     Some college  |   -.054266   .1270881    -0.43   0.669    -.3033541     .194822
                   Graduate study  |   -.018186   .0843838    -0.22   0.829    -.1835752    .1472031
                  Graduate degree  |  -.2479807   .0691808    -3.58   0.000    -.3835726   -.1123888
                                   |
                years_employ_state |   .0010563   .0042415     0.25   0.803    -.0072569    .0093694
               years_employ_agency |  -.0007916   .0044923    -0.18   0.860    -.0095963    .0080131
             years_employ_position |  -.0247561   .0062078    -3.99   0.000    -.0369232   -.0125889
                                   |
                              pid5 |
                       Republican  |   .1278304   .0864707     1.48   0.139    -.0416492    .2973099
                  Lean Republican  |   .0687908   .1097137     0.63   0.531    -.1462441    .2838257
                  Lean Democratic  |   .0815911   .1002059     0.81   0.416    -.1148089    .2779912
                       Democratic  |    .065322   .0791714     0.83   0.409    -.0898511     .220495
                                   |
                       agency_size |
                           25-100  |  -.1020634   .0807834    -1.26   0.206    -.2603959    .0562692
                          101-500  |  -.2622672   .0886803    -2.96   0.003    -.4360774   -.0884571
                        501-1,000  |  -.3807955   .1136747    -3.35   0.001    -.6035938   -.1579973
                      1,001-5,000  |  -.4358469   .1193842    -3.65   0.000    -.6698356   -.2018582
                       Over 5,000  |   -.466413   .1595789    -2.92   0.003    -.7791819   -.1536441
                                   |
                 log_agency_budget |   .0012167   .0195643     0.06   0.950    -.0371287    .0395621
                      inst6017_nom |  -.0038087   .0029601    -1.29   0.198    -.0096103     .001993
                                   |
                          funcat13 |
                    Staff: Fiscal  |   2.124618   .1818641    11.68   0.000      1.76817    2.481065
                Staff: Non-Fiscal  |   2.493533   .1820849    13.69   0.000     2.136654    2.850413
Income Security & Social Services  |      1.855   .1685816    11.00   0.000     1.524587    2.185414
                        Education  |   1.484903    .177558     8.36   0.000     1.136896    1.832911
                           Health  |   1.868607   .1774235    10.53   0.000     1.520864    2.216351
                Natural Resources  |   1.646815   .1603565    10.27   0.000     1.332522    1.961108
             Environment & Energy  |   1.743706    .165766    10.52   0.000      1.41881    2.068601
             Economic Development  |   1.721396   .1715692    10.03   0.000     1.385126    2.057665
                 Criminal Justice  |    1.75042   .1700014    10.30   0.000     1.417224    2.083617
                       Regulatory  |   1.200937   .1613258     7.44   0.000     .8847438    1.517129
                   Transportation  |   1.826961   .1788387    10.22   0.000     1.476443    2.177478
                            Other  |   1.797854    .174161    10.32   0.000     1.456504    2.139203
                                   |
                             state |
                               AK  |   1.082661   .2505263     4.32   0.000     .5916381    1.573683
                               AZ  |   .5358674   .2681436     2.00   0.046     .0103155    1.061419
                               AR  |   .7669651   .2597006     2.95   0.003     .2579613    1.275969
                               CA  |   1.183997   .3001309     3.94   0.000     .5957517    1.772243
                               CO  |  -.4967529     .24594    -2.02   0.043    -.9787865   -.0147194
                               CT  |   .3940912   .3048406     1.29   0.196    -.2033854    .9915678
                               DE  |    .476991   .2403071     1.98   0.047     .0059977    .9479843
                               FL  |   .6012339   .2569494     2.34   0.019     .0976223    1.104845
                               GA  |   .5573796   .2454144     2.27   0.023     .0763763    1.038383
                               HI  |   1.198756   .2602354     4.61   0.000     .6887035    1.708808
                               ID  |   .2417442   .2478666     0.98   0.329    -.2440654    .7275538
                               IL  |   .7088106   .2836916     2.50   0.012     .1527853    1.264836
                               IN  |   1.336694   .2515595     5.31   0.000     .8436469    1.829742
                               IA  |   .5559855   .2296182     2.42   0.015     .1059421    1.006029
                               KS  |   .4877769   .2638425     1.85   0.064    -.0293449    1.004899
                               KY  |   1.255336   .2647555     4.74   0.000     .7364249    1.774247
                               LA  |   .6105656   .2644045     2.31   0.021     .0923422    1.128789
                               ME  |   .0463092     .25591     0.18   0.856    -.4552653    .5478836
                               MD  |   .6060077   .2593598     2.34   0.019     .0976718    1.114344
                               MA  |    .893062   .2831452     3.15   0.002     .3381075    1.448016
                               MI  |   .9795158   .2487333     3.94   0.000     .4920075    1.467024
                               MN  |  -.0030547   .2338963    -0.01   0.990    -.4614829    .4553736
                               MS  |  -.3379897   .2711731    -1.25   0.213    -.8694793    .1934999
                               MO  |   .3819967   .2400152     1.59   0.111    -.0884244    .8524178
                               MT  |   .1827803   .2407363     0.76   0.448    -.2890541    .6546148
                               NE  |   .8011606   .2421027     3.31   0.001      .326648    1.275673
                               NV  |   .5596408   .2439547     2.29   0.022     .0814985    1.037783
                               NH  |   .0642769   .2556561     0.25   0.801    -.4367999    .5653536
                               NJ  |   1.255438   .2695879     4.66   0.000     .7270559    1.783821
                               NM  |   .4022057   .2610124     1.54   0.123    -.1093692    .9137806
                               NY  |   1.215348   .2946348     4.12   0.000     .6378749    1.792822
                               NC  |   .5109553   .2308856     2.21   0.027     .0584278    .9634828
                               ND  |   .2090441   .2447886     0.85   0.393    -.2707328     .688821
                               OH  |   .6331062   .2370992     2.67   0.008     .1684003    1.097812
                               OK  |   .7097933   .2537502     2.80   0.005     .2124521    1.207134
                               OR  |   .2320357    .234425     0.99   0.322     -.227429    .6915003
                               PA  |   1.323251   .2497802     5.30   0.000      .833691    1.812812
                               RI  |   .5613417   .2638543     2.13   0.033     .0441968    1.078487
                               SC  |   .0470551    .246041     0.19   0.848    -.4351764    .5292867
                               SD  |   .5831734    .246379     2.37   0.018     .1002794    1.066067
                               TN  |   .9640615   .2637284     3.66   0.000     .4471633     1.48096
                               TX  |  -.1015078   .2560205    -0.40   0.692    -.6032988    .4002832
                               UT  |   .6428746   .2322274     2.77   0.006     .1877172    1.098032
                               VT  |   .6846565   .2506185     2.73   0.006     .1934533     1.17586
                               VA  |   1.276843    .274723     4.65   0.000      .738396    1.815291
                               WA  |   .3305411   .2490028     1.33   0.184    -.1574953    .8185776
                               WV  |   .4697377   .2486516     1.89   0.059    -.0176104    .9570859
                               WI  |   .7184615   .2335875     3.08   0.002     .2606384    1.176285
                               WY  |   .8312287    .253885     3.27   0.001     .3336233    1.328834
                                   |
                              year |
                             1984  |  -.0498976   .0971933    -0.51   0.608     -.240393    .1405977
                             1988  |  -.1935672   .0927174    -2.09   0.037      -.37529   -.0118443
                             1994  |   .2769455   .0980994     2.82   0.005     .0846741    .4692168
                             1998  |   .4274018   .1021983     4.18   0.000     .2270968    .6277069
                             2004  |  -.0701028   .1057966    -0.66   0.508    -.2774603    .1372547
                             2008  |   .2888849     .11057     2.61   0.009     .0721716    .5055982
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -.8877279   .6542983                     -2.170129    .3946732
                             /cut2 |   1.281446   .6540547                     -.0004777     2.56337
                             /cut3 |   2.772505   .6546696                      1.489376    4.055634
----------------------------------------------------------------------------------------------------

. est sto m7

. 
. ologit d_21a i.intersection i.reve_1c i.reve_1d i.civil_service weekly_hours age age_2 b3.edu years_employ_
> state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fun
> cat13 i.state i.year , r 

Iteration 0:   log pseudolikelihood = -7690.3555  
Iteration 1:   log pseudolikelihood = -7467.7068  
Iteration 2:   log pseudolikelihood = -7466.6458  
Iteration 3:   log pseudolikelihood = -7466.6454  

Ordered logistic regression                     Number of obs     =      6,158
                                                Wald chi2(100)    =     426.80
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -7466.6454               Pseudo R2         =     0.0291

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_21a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.0786444   .0686608    -1.15   0.252    -.2132172    .0559283
                     Man of Color  |   .3410724   .0972086     3.51   0.000      .150547    .5315978
                   Woman of Color  |   .5717724   .1995998     2.86   0.004      .180564    .9629808
                                   |
                           reve_1c |
                Less than Monthly  |     .10925   .2831662     0.39   0.700    -.4457456    .6642456
                          Monthly  |   .0470158    .284686     0.17   0.869    -.5109584    .6049901
                           Weekly  |   .1109519   .2885238     0.38   0.701    -.4545443    .6764481
                            Daily  |   .0685312   .3025544     0.23   0.821    -.5244645    .6615269
                                   |
                           reve_1d |
                Less than Monthly  |    .718949   .2165388     3.32   0.001     .2945407    1.143357
                          Monthly  |   .8841762   .2169841     4.07   0.000     .4588952    1.309457
                           Weekly  |   .9600296   .2204581     4.35   0.000     .5279397    1.392119
                            Daily  |   1.183061   .2386773     4.96   0.000     .7152624     1.65086
                                   |
                     civil_service |
                              Yes  |   .0913557    .062857     1.45   0.146    -.0318418    .2145532
                      weekly_hours |   .0013429   .0031455     0.43   0.669    -.0048221     .007508
                               age |  -.0234925   .0248033    -0.95   0.344     -.072106    .0251211
                             age_2 |   .0002765   .0002472     1.12   0.263    -.0002081    .0007611
                                   |
                               edu |
              High school or less  |   .3188953   .2796582     1.14   0.254    -.2292247    .8670153
                     Some college  |  -.2334719   .1269448    -1.84   0.066    -.4822791    .0153353
                   Graduate study  |  -.0872736   .0854212    -1.02   0.307    -.2546961    .0801489
                  Graduate degree  |  -.2556885    .067743    -3.77   0.000    -.3884624   -.1229146
                                   |
                years_employ_state |  -.0051609   .0040345    -1.28   0.201    -.0130683    .0027465
               years_employ_agency |   .0058361   .0043168     1.35   0.176    -.0026246    .0142968
             years_employ_position |  -.0139081   .0064108    -2.17   0.030    -.0264731   -.0013431
                                   |
                              pid5 |
                       Republican  |  -.0199526   .0871332    -0.23   0.819    -.1907304    .1508253
                  Lean Republican  |   .0955725   .1101068     0.87   0.385    -.1202328    .3113778
                  Lean Democratic  |   .1091993   .1020077     1.07   0.284    -.0907322    .3091308
                       Democratic  |   .0064929   .0795586     0.08   0.935    -.1494391     .162425
                                   |
                       agency_size |
                           25-100  |   .1225227   .0817088     1.50   0.134    -.0376236     .282669
                          101-500  |   .1092047   .0895476     1.22   0.223    -.0663054    .2847147
                        501-1,000  |  -.0804772   .1134495    -0.71   0.478    -.3028342    .1418798
                      1,001-5,000  |  -.0954097   .1189733    -0.80   0.423     -.328593    .1377736
                       Over 5,000  |  -.1316604   .1577497    -0.83   0.404    -.4408442    .1775233
                                   |
                 log_agency_budget |   .0190175   .0199765     0.95   0.341    -.0201357    .0581707
                      inst6017_nom |   .0036674   .0029984     1.22   0.221    -.0022095    .0095442
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .2065958    .177017     1.17   0.243    -.1403511    .5535427
                Staff: Non-Fiscal  |    .324499   .1863147     1.74   0.082    -.0406712    .6896691
Income Security & Social Services  |   .1536282    .168862     0.91   0.363    -.1773353    .4845917
                        Education  |   .1997398   .1788496     1.12   0.264    -.1507989    .5502785
                           Health  |   .2854157    .175847     1.62   0.105    -.0592381    .6300695
                Natural Resources  |   .3496089   .1602327     2.18   0.029     .0355586    .6636592
             Environment & Energy  |   .4458211   .1675439     2.66   0.008      .117441    .7742012
             Economic Development  |   .1203173   .1717747     0.70   0.484    -.2163549    .4569895
                 Criminal Justice  |  -.0118803    .172643    -0.07   0.945    -.3502544    .3264937
                       Regulatory  |   .0430467   .1620853     0.27   0.791    -.2746347     .360728
                   Transportation  |   .4118565   .1791851     2.30   0.022     .0606601    .7630529
                            Other  |   .2781264   .1731409     1.61   0.108    -.0612235    .6174763
                                   |
                             state |
                               AK  |    .151369   .2273822     0.67   0.506     -.294292      .59703
                               AZ  |   .1664503   .2542532     0.65   0.513    -.3318768    .6647773
                               AR  |   .7847349   .2462332     3.19   0.001     .3021267    1.267343
                               CA  |   .1623595   .2532019     0.64   0.521    -.3339071    .6586261
                               CO  |   .0201354   .2315585     0.09   0.931    -.4337109    .4739816
                               CT  |   .9054051   .2993957     3.02   0.002     .3186003     1.49221
                               DE  |   .2269869   .2331822     0.97   0.330    -.2300418    .6840156
                               FL  |   .5703886   .2537443     2.25   0.025      .073059    1.067718
                               GA  |   .2438811   .2367349     1.03   0.303    -.2201108     .707873
                               HI  |  -.2847697   .2489876    -1.14   0.253    -.7727764     .203237
                               ID  |   .8395376   .2350622     3.57   0.000     .3788242    1.300251
                               IL  |   .3553761   .2550335     1.39   0.163    -.1444804    .8552326
                               IN  |   .2373381   .2449609     0.97   0.333    -.2427763    .7174526
                               IA  |   .8997025   .2131424     4.22   0.000     .4819511    1.317454
                               KS  |   1.002167   .2447644     4.09   0.000     .5224371    1.481896
                               KY  |   1.031324   .2377848     4.34   0.000     .5652739    1.497373
                               LA  |   .4511873   .2578284     1.75   0.080     -.054147    .9565217
                               ME  |   .2937345   .2526956     1.16   0.245    -.2015398    .7890087
                               MD  |   .6435443     .24484     2.63   0.009     .1636667    1.123422
                               MA  |  -.1271917   .2368022    -0.54   0.591    -.5913154     .336932
                               MI  |   .9426299   .2379379     3.96   0.000     .4762802     1.40898
                               MN  |   .0907566    .222522     0.41   0.683    -.3453784    .5268917
                               MS  |   .4752427   .2492823     1.91   0.057    -.0133416    .9638271
                               MO  |   .2561405   .2216214     1.16   0.248    -.1782295    .6905105
                               MT  |    .050391   .2218922     0.23   0.820    -.3845098    .4852917
                               NE  |   .2033564   .2425497     0.84   0.402    -.2720322     .678745
                               NV  |   .3883154   .2426197     1.60   0.109    -.0872104    .8638411
                               NH  |   1.111596   .2500697     4.45   0.000     .6214682    1.601724
                               NJ  |   .4530862   .2554318     1.77   0.076     -.047551    .9537234
                               NM  |  -.3530254   .2481271    -1.42   0.155    -.8393455    .1332948
                               NY  |   .2095196   .2816958     0.74   0.457     -.342594    .7616332
                               NC  |   .4407452   .2256766     1.95   0.051    -.0015728    .8830632
                               ND  |   .2852265   .2289199     1.25   0.213    -.1634483    .7339013
                               OH  |   .6693656   .2359473     2.84   0.005     .2069174    1.131814
                               OK  |   .8321741   .2348963     3.54   0.000     .3717859    1.292562
                               OR  |    .096219   .2260651     0.43   0.670    -.3468604    .5392983
                               PA  |   .2486274   .2443457     1.02   0.309    -.2302814    .7275361
                               RI  |   .0582583   .2451435     0.24   0.812    -.4222141    .5387308
                               SC  |   1.110323   .2801679     3.96   0.000     .5612037    1.659442
                               SD  |   .2217329   .2536966     0.87   0.382    -.2755034    .7189691
                               TN  |   .8347342   .2414505     3.46   0.001        .3615    1.307969
                               TX  |   .6655271   .2598144     2.56   0.010     .1563002    1.174754
                               UT  |   .4863982   .2233808     2.18   0.029       .04858    .9242165
                               VT  |   .7888288   .2363864     3.34   0.001     .3255201    1.252138
                               VA  |    .410458   .2701896     1.52   0.129    -.1191038    .9400198
                               WA  |  -.1194843   .2278186    -0.52   0.600    -.5660007     .327032
                               WV  |   1.082288   .2415445     4.48   0.000     .6088699    1.555707
                               WI  |   .8547203   .2227618     3.84   0.000     .4181153    1.291325
                               WY  |   .4220065   .2342584     1.80   0.072    -.0371315    .8811446
                                   |
                              year |
                             1984  |  -.2033245   .0932245    -2.18   0.029     -.386041   -.0206079
                             1988  |  -.1906196   .0904932    -2.11   0.035     -.367983   -.0132562
                             1994  |   .0739387    .094504     0.78   0.434    -.1112856    .2591631
                             1998  |   .2198158   .0999717     2.20   0.028     .0238749    .4157568
                             2004  |  -.1682372   .1070404    -1.57   0.116    -.3780326    .0415581
                             2008  |   .2292203   .1108334     2.07   0.039     .0119908    .4464498
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.591533   .7508827                     -3.063236   -.1198298
                             /cut2 |   .7532006   .7474952                      -.711863    2.218264
                             /cut3 |   2.402633   .7477095                      .9371495    3.868117
----------------------------------------------------------------------------------------------------

. est sto m8 

.  
.  
.   esttab m5 m6 m7 m8 using Table_3.rtf ,starlevels(+ 0.10 * 0.05 ** 0.01) cells(b(star fmt(3)) se(par fmt(3
> ))) ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Gov. Policy" "Legis. Policy" "Gov. Regs" "Legis. Regs")
(output written to Table_3.rtf)

. 
. ***** CODE USED TO PRODUCE FIGURE 1 PANEL A ******
. 
. est restore m5
(results m5 are active now)

. margins, dydx(intersection)

Average marginal effects                        Number of obs     =      6,224
Model VCE    : Robust

dy/dx w.r.t. : 1.intersection 2.intersection 3.intersection
1._predict   : Pr(d_15a==0), predict(pr outcome(0))
2._predict   : Pr(d_15a==1), predict(pr outcome(1))
3._predict   : Pr(d_15a==2), predict(pr outcome(2))
4._predict   : Pr(d_15a==3), predict(pr outcome(3))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
0.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
1.intersection  |
       _predict |
             1  |   .0036451    .002401     1.52   0.129    -.0010607     .008351
             2  |   .0113297   .0072553     1.56   0.118    -.0028904    .0255498
             3  |   .0106679   .0065694     1.62   0.104    -.0022078    .0235437
             4  |  -.0256428   .0162002    -1.58   0.113    -.0573946    .0061091
----------------+----------------------------------------------------------------
2.intersection  |
       _predict |
             1  |  -.0073611   .0026197    -2.81   0.005    -.0124957   -.0022265
             2  |  -.0247303   .0091464    -2.70   0.007    -.0426569   -.0068038
             3  |  -.0280835    .011486    -2.45   0.014    -.0505957   -.0055713
             4  |    .060175   .0231587     2.60   0.009     .0147847    .1055652
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |  -.0122091    .004107    -2.97   0.003    -.0202587   -.0041594
             2  |  -.0426021   .0156453    -2.72   0.006    -.0732664   -.0119379
             3  |  -.0530481   .0235137    -2.26   0.024    -.0991342    -.006962
             4  |   .1078593   .0431054     2.50   0.012     .0233744    .1923443
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. mplotoffset, recast(scatter) title(Governor) xtitle(Influence on Major Policy Decisions) xlabel(2 "White Wo
> man" 3 "Man of Color" 4 "Woman of Color", labsize(small)) legend(rows(1) stack size(small)) legend(order ( 
> 5 "None" 6 "Slight" 7 "Moderate" 8 "High")) aspect(0.9)

  Variables that uniquely identify margins: _deriv _outcome

. 
. graph save figure_1a
(file figure_1a.gph saved)

.  
. 
. ***** CODE USED TO PRODUCE FIGURE 1 PANEL B ******
. 
. est restore m6
(results m6 are active now)

. margins, dydx(intersection)

Average marginal effects                        Number of obs     =      6,200
Model VCE    : Robust

dy/dx w.r.t. : 1.intersection 2.intersection 3.intersection
1._predict   : Pr(d_16a==0), predict(pr outcome(0))
2._predict   : Pr(d_16a==1), predict(pr outcome(1))
3._predict   : Pr(d_16a==2), predict(pr outcome(2))
4._predict   : Pr(d_16a==3), predict(pr outcome(3))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
0.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
1.intersection  |
       _predict |
             1  |  -.0007241   .0013964    -0.52   0.604     -.003461    .0020128
             2  |  -.0040557   .0078742    -0.52   0.607    -.0194888    .0113773
             3  |  -.0038899   .0076821    -0.51   0.613    -.0189465    .0111668
             4  |   .0086697   .0169496     0.51   0.609     -.024551    .0418903
----------------+----------------------------------------------------------------
2.intersection  |
       _predict |
             1  |  -.0044977   .0018141    -2.48   0.013    -.0080533   -.0009422
             2  |  -.0261254   .0106945    -2.44   0.015    -.0470863   -.0051645
             3  |  -.0290486   .0136413    -2.13   0.033    -.0557851   -.0023122
             4  |   .0596718   .0260591     2.29   0.022     .0085969    .1107467
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |  -.0070444   .0028893    -2.44   0.015    -.0127073   -.0013815
             2  |  -.0419698   .0180102    -2.33   0.020    -.0772692   -.0066704
             3  |   -.051885   .0281797    -1.84   0.066    -.1071161    .0033462
             4  |   .1008991   .0489431     2.06   0.039     .0049724    .1968258
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. mplotoffset, recast(scatter) title(Legislature) xtitle(Influence on Major Policy Decisions) xlabel(2 "White
>  Woman" 3 "Man of Color" 4 "Woman of Color", labsize(small)) legend(rows(1) stack size(small)) legend(order
>  ( 5 "None" 6 "Slight" 7 "Moderate" 8 "High")) aspect(0.9)

  Variables that uniquely identify margins: _deriv _outcome

. 
. graph save figure_1b
(file figure_1b.gph saved)

. 
. ***** CODE USED TO PRODUCE FIGURE 2 PANEL A ******
. 
. est restore m7
(results m7 are active now)

. margins, dydx(intersection)

Average marginal effects                        Number of obs     =      6,175
Model VCE    : Robust

dy/dx w.r.t. : 1.intersection 2.intersection 3.intersection
1._predict   : Pr(d_20a==0), predict(pr outcome(0))
2._predict   : Pr(d_20a==1), predict(pr outcome(1))
3._predict   : Pr(d_20a==2), predict(pr outcome(2))
4._predict   : Pr(d_20a==3), predict(pr outcome(3))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
0.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
1.intersection  |
       _predict |
             1  |   .0176732   .0058032     3.05   0.002     .0062991    .0290473
             2  |   .0306955   .0093454     3.28   0.001     .0123789    .0490121
             3  |  -.0087742   .0032699    -2.68   0.007    -.0151831   -.0023653
             4  |  -.0395945   .0118993    -3.33   0.001    -.0629168   -.0162722
----------------+----------------------------------------------------------------
2.intersection  |
       _predict |
             1  |  -.0139429    .006528    -2.14   0.033    -.0267376   -.0011483
             2  |  -.0292142   .0147215    -1.98   0.047    -.0580677   -.0003606
             3  |   .0035361   .0010369     3.41   0.001     .0015037    .0055685
             4  |    .039621   .0203898     1.94   0.052    -.0003423    .0795843
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |  -.0301042   .0097545    -3.09   0.002    -.0492227   -.0109858
             2  |  -.0700253   .0269664    -2.60   0.009    -.1228784   -.0171722
             3  |   .0007753   .0048361     0.16   0.873    -.0087032    .0102538
             4  |   .0993542   .0412306     2.41   0.016     .0185437    .1801648
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. mplotoffset, recast(scatter) title(Governor) xtitle(Influence on Rules and Regulations) xlabel(2 "White Wom
> an" 3 "Man of Color" 4 "Woman of Color", labsize(small)) legend(rows(1) stack size(small)) legend(order ( 5
>  "None" 6 "Slight" 7 "Moderate" 8 "High")) aspect(0.9)

  Variables that uniquely identify margins: _deriv _outcome

. 
. graph save figure_2a
(file figure_2a.gph saved)

. 
. 
. ***** CODE USED TO PRODUCE FIGURE 2 PANEL B ******
. 
. est restore m8
(results m8 are active now)

. margins, dydx(intersection)

Average marginal effects                        Number of obs     =      6,158
Model VCE    : Robust

dy/dx w.r.t. : 1.intersection 2.intersection 3.intersection
1._predict   : Pr(d_21a==0), predict(pr outcome(0))
2._predict   : Pr(d_21a==1), predict(pr outcome(1))
3._predict   : Pr(d_21a==2), predict(pr outcome(2))
4._predict   : Pr(d_21a==3), predict(pr outcome(3))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
0.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
1.intersection  |
       _predict |
             1  |    .004564     .00407     1.12   0.262     -.003413     .012541
             2  |   .0131328   .0114633     1.15   0.252    -.0093349    .0356004
             3  |  -.0037565   .0035132    -1.07   0.285    -.0106423    .0031293
             4  |  -.0139403   .0120243    -1.16   0.246    -.0375074    .0096268
----------------+----------------------------------------------------------------
2.intersection  |
       _predict |
             1  |   -.016575   .0042572    -3.89   0.000    -.0249189    -.008231
             2  |  -.0563401   .0157179    -3.58   0.000    -.0871466   -.0255336
             3  |   .0068331   .0012489     5.47   0.000     .0043853    .0092808
             4  |    .066082   .0197843     3.34   0.001     .0273054    .1048586
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |  -.0252605   .0069637    -3.63   0.000     -.038909    -.011612
             2  |  -.0925263   .0303455    -3.05   0.002    -.1520024   -.0330503
             3  |   .0024637   .0068313     0.36   0.718    -.0109253    .0158527
             4  |   .1153231   .0436626     2.64   0.008     .0297459    .2009002
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. mplotoffset, recast(scatter) title(Legislature) xtitle(Influence on Rules and Regulations) xlabel(2 "White 
> Woman" 3 "Man of Color" 4 "Woman of Color", labsize(small)) legend(rows(1) stack size(small)) legend(order 
> ( 5 "None" 6 "Slight" 7 "Moderate" 8 "High")) aspect(0.9)

  Variables that uniquely identify margins: _deriv _outcome

. 
. graph save figure_2b
(file figure_2b.gph saved)

. 
. ***** TO CALCULATE TABLE NOTES FOR EACH GRAPH RUN THE FOLLOWING ****
. *** 1A ***
. est restore m5
(results m5 are active now)

. test i0.intersection=i3.intersection

 ( 1)  [d_15a]0b.intersection - [d_15a]3.intersection = 0

           chi2(  1) =    5.53
         Prob > chi2 =    0.0186

. test i1.intersection=i3.intersection

 ( 1)  [d_15a]1.intersection - [d_15a]3.intersection = 0

           chi2(  1) =    7.92
         Prob > chi2 =    0.0049

. test i2.intersection=i3.intersection

 ( 1)  [d_15a]2.intersection - [d_15a]3.intersection = 0

           chi2(  1) =    0.99
         Prob > chi2 =    0.3188

. *** 1B ***
. est restore m6
(results m6 are active now)

. test i0.intersection=i3.intersection

 ( 1)  [d_16a]0b.intersection - [d_16a]3.intersection = 0

           chi2(  1) =    4.13
         Prob > chi2 =    0.0421

. test i1.intersection=i3.intersection

 ( 1)  [d_16a]1.intersection - [d_16a]3.intersection = 0

           chi2(  1) =    3.30
         Prob > chi2 =    0.0692

. test i2.intersection=i3.intersection

 ( 1)  [d_16a]2.intersection - [d_16a]3.intersection = 0

           chi2(  1) =    0.59
         Prob > chi2 =    0.4408

. *** 2A ***
. est restore m7
(results m7 are active now)

. test i0.intersection=i3.intersection

 ( 1)  [d_20a]0b.intersection - [d_20a]3.intersection = 0

           chi2(  1) =    6.52
         Prob > chi2 =    0.0107

. test i1.intersection=i3.intersection

 ( 1)  [d_20a]1.intersection - [d_20a]3.intersection = 0

           chi2(  1) =   13.00
         Prob > chi2 =    0.0003

. test i2.intersection=i3.intersection

 ( 1)  [d_20a]2.intersection - [d_20a]3.intersection = 0

           chi2(  1) =    1.89
         Prob > chi2 =    0.1690

. *** 2B ***
. est restore m8
(results m8 are active now)

. test i0.intersection=i3.intersection

 ( 1)  [d_21a]0b.intersection - [d_21a]3.intersection = 0

           chi2(  1) =    8.21
         Prob > chi2 =    0.0042

. test i1.intersection=i3.intersection

 ( 1)  [d_21a]1.intersection - [d_21a]3.intersection = 0

           chi2(  1) =   10.17
         Prob > chi2 =    0.0014

. test i2.intersection=i3.intersection

 ( 1)  [d_21a]2.intersection - [d_21a]3.intersection = 0

           chi2(  1) =    1.19
         Prob > chi2 =    0.2755

. 
. *** RESULTS EXPORTED AND FORMATTED INTO FIGURES 1 & 2 ***
. 
. ************************************************
. *** REPLICATION CODE FOR SUPPLIMENTAL TABLES ***
. ************************************************
. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B1 ******
. 
. ologit reve_1a b1.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_emplo
> y_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.ye
> ar , r 

Iteration 0:   log pseudolikelihood = -10356.699  
Iteration 1:   log pseudolikelihood = -8819.4854  
Iteration 2:   log pseudolikelihood = -8749.2319  
Iteration 3:   log pseudolikelihood = -8749.0873  
Iteration 4:   log pseudolikelihood = -8749.0873  

Ordered logistic regression                     Number of obs     =      7,515
                                                Wald chi2(93)     =    2873.27
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -8749.0873               Pseudo R2         =     0.1552

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                        White Man  |   .2422217   .0706904     3.43   0.001     .1036711    .3807723
                     Man of Color  |   .1064623   .1157943     0.92   0.358    -.1204905     .333415
                   Woman of Color  |  -.2851912   .1763967    -1.62   0.106    -.6309225    .0605401
                                   |
                     civil_service |
                              Yes  |   -.971733   .0600389   -16.19   0.000    -1.089407   -.8540589
                      weekly_hours |   .0521346   .0031106    16.76   0.000     .0460381    .0582312
                               age |  -.0374195   .0224833    -1.66   0.096    -.0814859    .0066468
                             age_2 |     .00053   .0002215     2.39   0.017     .0000957    .0009642
                                   |
                               edu |
              High school or less  |   .0306371   .1979765     0.15   0.877    -.3573896    .4186638
                     Some college  |   .1162062   .1062374     1.09   0.274    -.0920154    .3244277
                   Graduate study  |   .0538401    .077269     0.70   0.486    -.0976045    .2052846
                  Graduate degree  |  -.0971884   .0647571    -1.50   0.133    -.2241101    .0297332
                                   |
                years_employ_state |   -.000374   .0041522    -0.09   0.928    -.0085121    .0077642
               years_employ_agency |  -.0313019    .004373    -7.16   0.000    -.0398728    -.022731
             years_employ_position |   .0076163   .0054818     1.39   0.165    -.0031279    .0183605
                                   |
                              pid5 |
                       Republican  |    .481098   .0819153     5.87   0.000     .3205471     .641649
                  Lean Republican  |   .1207507   .1017217     1.19   0.235    -.0786201    .3201215
                  Lean Democratic  |  -.0231355   .0978389    -0.24   0.813    -.2148963    .1686252
                       Democratic  |    .473495   .0747023     6.34   0.000     .3270812    .6199088
                                   |
                       agency_size |
                           25-100  |   .1619845   .0731383     2.21   0.027     .0186361    .3053329
                          101-500  |   .5105166   .0842327     6.06   0.000     .3454235    .6756097
                        501-1,000  |   .7649114   .1109232     6.90   0.000     .5475059    .9823169
                      1,001-5,000  |   1.068553   .1151358     9.28   0.000     .8428913    1.294215
                       Over 5,000  |   1.494491   .1556228     9.60   0.000     1.189476    1.799506
                                   |
                 log_agency_budget |   .1757835   .0201581     8.72   0.000     .1362744    .2152926
                      inst6017_nom |  -.0030011   .0028368    -1.06   0.290    -.0085611     .002559
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .6925461   .1617936     4.28   0.000     .3754364    1.009656
                Staff: Non-Fiscal  |  -.2202206    .157977    -1.39   0.163    -.5298497    .0894086
Income Security & Social Services  |   -1.47653    .136935   -10.78   0.000    -1.744918   -1.208143
                        Education  |  -.9776317   .1461753    -6.69   0.000     -1.26413   -.6911333
                           Health  |  -1.648944   .1473031   -11.19   0.000    -1.937653   -1.360235
                Natural Resources  |  -.7923242   .1261825    -6.28   0.000    -1.039637   -.5450112
             Environment & Energy  |  -.7873803   .1351057    -5.83   0.000    -1.052183   -.5225781
             Economic Development  |   .0223083   .1390922     0.16   0.873    -.2503073     .294924
                 Criminal Justice  |  -.9552778   .1347269    -7.09   0.000    -1.219338   -.6912179
                       Regulatory  |  -1.257715   .1303817    -9.65   0.000    -1.513259   -1.002172
                   Transportation  |    -1.0062   .1410028    -7.14   0.000    -1.282561     -.72984
                            Other  |   -.757503    .137055    -5.53   0.000    -1.026126   -.4888801
                                   |
                             state |
                               AK  |  -.3341416   .2197752    -1.52   0.128    -.7648931    .0966098
                               AZ  |  -1.072071   .2452188    -4.37   0.000    -1.552691   -.5914514
                               AR  |  -.2319074   .2038058    -1.14   0.255    -.6313594    .1675447
                               CA  |  -2.499601   .2436337   -10.26   0.000    -2.977114   -2.022088
                               CO  |  -.0331212   .2128896    -0.16   0.876    -.4503771    .3841348
                               CT  |  -1.157115   .2515839    -4.60   0.000     -1.65021   -.6640194
                               DE  |   -.367357   .2112314    -1.74   0.082     -.781363    .0466489
                               FL  |  -1.685318   .2436817    -6.92   0.000    -2.162925   -1.207711
                               GA  |  -.9216965   .2307668    -3.99   0.000    -1.373991   -.4694019
                               HI  |  -.7774421   .2439012    -3.19   0.001     -1.25548   -.2994046
                               ID  |   .2447971   .2047634     1.20   0.232    -.1565316    .6461259
                               IL  |  -1.432487   .2441575    -5.87   0.000    -1.911027   -.9539475
                               IN  |  -.5692946    .230641    -2.47   0.014    -1.021343   -.1172465
                               IA  |  -.2820726   .1985466    -1.42   0.155    -.6712168    .1070717
                               KS  |  -.4032152    .227537    -1.77   0.076    -.8491795    .0427492
                               KY  |  -1.063754   .2289834    -4.65   0.000    -1.512553   -.6149547
                               LA  |  -.8155946   .2608939    -3.13   0.002    -1.326937   -.3042519
                               ME  |  -.0783662   .2253939    -0.35   0.728    -.5201302    .3633978
                               MD  |  -.9876069   .2317822    -4.26   0.000    -1.441892   -.5333221
                               MA  |  -1.693045   .2448103    -6.92   0.000    -2.172865   -1.213226
                               MI  |   -.874717     .21754    -4.02   0.000    -1.301088   -.4483464
                               MN  |  -1.107307   .2253961    -4.91   0.000    -1.549075   -.6655391
                               MS  |  -.2822958   .2248794    -1.26   0.209    -.7230512    .1584597
                               MO  |  -1.220202   .2130826    -5.73   0.000    -1.637836   -.8025675
                               MT  |   .1358397   .2015739     0.67   0.500    -.2592379    .5309173
                               NE  |   .1869023   .2290752     0.82   0.415     -.262077    .6358815
                               NV  |  -.2360691   .2123013    -1.11   0.266     -.652172    .1800339
                               NH  |  -.0685534   .2225901    -0.31   0.758    -.5048219    .3677151
                               NJ  |  -1.228063   .2328847    -5.27   0.000    -1.684509   -.7716174
                               NM  |   .0465281   .2273325     0.20   0.838    -.3990354    .4920916
                               NY  |  -2.188579   .2690821    -8.13   0.000    -2.715971   -1.661188
                               NC  |  -1.032744   .1957113    -5.28   0.000    -1.416331   -.6491567
                               ND  |   .6604772    .205922     3.21   0.001     .2568774    1.064077
                               OH  |  -1.235707   .2358003    -5.24   0.000    -1.697867   -.7735465
                               OK  |  -.6671675   .2154399    -3.10   0.002    -1.089422   -.2449129
                               OR  |  -.2735063   .2181166    -1.25   0.210     -.701007    .1539945
                               PA  |  -1.880874   .2278246    -8.26   0.000    -2.327402   -1.434346
                               RI  |   .2145086    .226937     0.95   0.345    -.2302797    .6592969
                               SC  |  -.5503567   .2137538    -2.57   0.010    -.9693065   -.1314069
                               SD  |   .3450091   .2136162     1.62   0.106     -.073671    .7636891
                               TN  |  -1.180326   .2327253    -5.07   0.000    -1.636459   -.7241927
                               TX  |  -1.979577   .2153058    -9.19   0.000    -2.401568   -1.557585
                               UT  |   .0487906   .2036328     0.24   0.811    -.3503224    .4479036
                               VT  |    .260382   .2111284     1.23   0.217    -.1534221     .674186
                               VA  |  -1.115041   .2323401    -4.80   0.000    -1.570419   -.6596628
                               WA  |  -.9946893   .2303605    -4.32   0.000    -1.446187   -.5431911
                               WV  |  -.5057771   .2176936    -2.32   0.020    -.9324488   -.0791055
                               WI  |  -.4418259   .2162913    -2.04   0.041    -.8657491   -.0179028
                               WY  |   .5443989   .1957128     2.78   0.005     .1608089    .9279889
                                   |
                              year |
                             1978  |  -.6629782    .087449    -7.58   0.000    -.8343751   -.4915813
                             1984  |   -.673541   .0838074    -8.04   0.000    -.8378006   -.5092815
                             1988  |  -.9775924   .0794303   -12.31   0.000    -1.133273   -.8219118
                             1994  |  -.8358436   .0852362    -9.81   0.000    -1.002904   -.6687837
                             1998  |  -1.171177   .0918104   -12.76   0.000    -1.351122    -.991232
                             2004  |  -1.224451    .095131   -12.87   0.000    -1.410904   -1.037997
                             2008  |  -1.507369   .1216842   -12.39   0.000    -1.745865   -1.268872
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.263173   .6288625                     -2.495721   -.0306251
                             /cut2 |   1.379438   .6283965                      .1478035    2.611072
                             /cut3 |   2.856489   .6297282                      1.622244    4.090733
                             /cut4 |   5.372229   .6378341                      4.122097    6.622361
----------------------------------------------------------------------------------------------------

. est sto a1

. 
. ologit reve_1b b1.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_emplo
> y_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.ye
> ar , r 

Iteration 0:   log pseudolikelihood = -9204.7672  
Iteration 1:   log pseudolikelihood = -8101.5966  
Iteration 2:   log pseudolikelihood = -8073.7021  
Iteration 3:   log pseudolikelihood = -8073.6594  
Iteration 4:   log pseudolikelihood = -8073.6594  

Ordered logistic regression                     Number of obs     =      6,378
                                                Wald chi2(92)     =    2018.62
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -8073.6594               Pseudo R2         =     0.1229

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1b |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                        White Man  |   .1502099   .0666871     2.25   0.024     .0195055    .2809143
                     Man of Color  |   .0934381   .1140126     0.82   0.412    -.1300225    .3168987
                   Woman of Color  |  -.3721929   .1741429    -2.14   0.033    -.7135068   -.0308791
                                   |
                     civil_service |
                              Yes  |  -.8010587   .0607996   -13.18   0.000    -.9202237   -.6818938
                      weekly_hours |   .0479222   .0033269    14.40   0.000     .0414016    .0544429
                               age |  -.0767768   .0231595    -3.32   0.001    -.1221687   -.0313849
                             age_2 |   .0007002   .0002276     3.08   0.002     .0002542    .0011462
                                   |
                               edu |
              High school or less  |   .2658405   .2268917     1.17   0.241     -.178859    .7105401
                     Some college  |   .1530398   .1191205     1.28   0.199    -.0804321    .3865117
                   Graduate study  |   .1476438   .0824394     1.79   0.073    -.0139344     .309222
                  Graduate degree  |   .0734268   .0687729     1.07   0.286    -.0613655    .2082192
                                   |
                years_employ_state |   .0056667   .0042638     1.33   0.184    -.0026902    .0140235
               years_employ_agency |  -.0282912   .0044624    -6.34   0.000    -.0370375    -.019545
             years_employ_position |  -.0066664    .005934    -1.12   0.261    -.0182968     .004964
                                   |
                              pid5 |
                       Republican  |   .3837354   .0851776     4.51   0.000     .2167903    .5506805
                  Lean Republican  |   .0228367   .1080157     0.21   0.833    -.1888702    .2345436
                  Lean Democratic  |  -.0635507   .0975554    -0.65   0.515    -.2547557    .1276544
                       Democratic  |   .3259516   .0797447     4.09   0.000      .169655    .4822483
                                   |
                       agency_size |
                           25-100  |  -.0445093   .0785051    -0.57   0.571    -.1983765     .109358
                          101-500  |   .1968848   .0895371     2.20   0.028     .0213954    .3723743
                        501-1,000  |   .3376189   .1193704     2.83   0.005     .1036573    .5715805
                      1,001-5,000  |   .6280194   .1251758     5.02   0.000     .3826794    .8733594
                       Over 5,000  |   1.022571   .1730498     5.91   0.000     .6833995    1.361742
                                   |
                 log_agency_budget |   .1899252   .0216562     8.77   0.000     .1474799    .2323705
                      inst6017_nom |   .0028871   .0031288     0.92   0.356    -.0032452    .0090195
                                   |
                          funcat13 |
                    Staff: Fiscal  |   1.405647   .1764997     7.96   0.000     1.059714     1.75158
                Staff: Non-Fiscal  |   .9466027    .184014     5.14   0.000     .5859419    1.307263
Income Security & Social Services  |  -.4537725   .1521941    -2.98   0.003    -.7520675   -.1554774
                        Education  |  -.4254235   .1625536    -2.62   0.009    -.7440227   -.1068244
                           Health  |  -.6096505   .1594823    -3.82   0.000    -.9222301   -.2970709
                Natural Resources  |  -.0851974   .1438454    -0.59   0.554    -.3671291    .1967344
             Environment & Energy  |   .0260771   .1494181     0.17   0.861    -.2667771    .3189312
             Economic Development  |   .7596595   .1528347     4.97   0.000     .4601089     1.05921
                 Criminal Justice  |   .0158167    .152794     0.10   0.918     -.283654    .3152875
                       Regulatory  |  -.6198936   .1436041    -4.32   0.000    -.9013524   -.3384348
                   Transportation  |  -.2217456   .1602336    -1.38   0.166    -.5357977    .0923064
                            Other  |   .1386793   .1519915     0.91   0.362    -.1592186    .4365771
                                   |
                             state |
                               AK  |  -.0763772   .2326042    -0.33   0.743     -.532273    .3795186
                               AZ  |  -.3752213   .2390634    -1.57   0.117     -.843777    .0933344
                               AR  |   .3394096   .2251537     1.51   0.132    -.1018836    .7807027
                               CA  |  -1.533002   .2558924    -5.99   0.000    -2.034542   -1.031462
                               CO  |  -.2716633   .2251548    -1.21   0.228    -.7129587     .169632
                               CT  |  -.8201582   .2658149    -3.09   0.002    -1.341146   -.2991707
                               DE  |   -.853052   .2246583    -3.80   0.000    -1.293374   -.4127299
                               FL  |  -1.320788   .2392821    -5.52   0.000    -1.789772   -.8518035
                               GA  |  -.8142959   .2564716    -3.17   0.001    -1.316971   -.3116208
                               HI  |  -1.396295    .267658    -5.22   0.000    -1.920895   -.8716948
                               ID  |    .726494   .2240838     3.24   0.001     .2872977     1.16569
                               IL  |  -.3944151   .2884722    -1.37   0.172    -.9598101      .17098
                               IN  |   .1277181   .2342384     0.55   0.586    -.3313807    .5868169
                               IA  |  -.3074279   .2208542    -1.39   0.164    -.7402941    .1254384
                               KS  |  -.5489781   .2269473    -2.42   0.016    -.9937866   -.1041696
                               KY  |  -.8118887   .2374382    -3.42   0.001    -1.277259   -.3465183
                               LA  |  -.3434393   .2497323    -1.38   0.169    -.8329057     .146027
                               ME  |   .1849485   .2444892     0.76   0.449    -.2942415    .6641386
                               MD  |  -.4369056   .2364424    -1.85   0.065    -.9003242     .026513
                               MA  |  -1.065537   .2666702    -4.00   0.000    -1.588201   -.5428731
                               MI  |  -.3496174   .2366052    -1.48   0.140     -.813355    .1141203
                               MN  |  -.9795967   .2251528    -4.35   0.000    -1.420888   -.5383054
                               MS  |  -.5658047   .2489902    -2.27   0.023    -1.053816   -.0777929
                               MO  |  -1.091504   .2314149    -4.72   0.000    -1.545069   -.6379394
                               MT  |   .1691514   .2047438     0.83   0.409     -.232139    .5704417
                               NE  |  -.2307015   .2256076    -1.02   0.307    -.6728842    .2114812
                               NV  |  -.2566648   .2268787    -1.13   0.258    -.7013389    .1880093
                               NH  |   .0673188   .2417316     0.28   0.781    -.4064663     .541104
                               NJ  |   -.835969   .2586301    -3.23   0.001    -1.342875   -.3290633
                               NM  |  -.2578871   .2347796    -1.10   0.272    -.7180467    .2022725
                               NY  |  -.2012437   .3048449    -0.66   0.509    -.7987287    .3962413
                               NC  |  -.9560659   .2161627    -4.42   0.000    -1.379737   -.5323947
                               ND  |   .2226899   .2054266     1.08   0.278    -.1799388    .6253187
                               OH  |  -.9561178   .2358251    -4.05   0.000    -1.418327    -.493909
                               OK  |  -.7989965   .2279037    -3.51   0.000     -1.24568   -.3523134
                               OR  |  -.3182658   .2248575    -1.42   0.157    -.7589785    .1224469
                               PA  |  -1.466266   .2569792    -5.71   0.000    -1.969936   -.9625957
                               RI  |   .3960384    .240397     1.65   0.099     -.075131    .8672078
                               SC  |   -.434628   .2319624    -1.87   0.061     -.889266      .02001
                               SD  |    .076803   .2277228     0.34   0.736    -.3695255    .5231314
                               TN  |  -1.131338   .2350654    -4.81   0.000    -1.592058   -.6706184
                               TX  |  -1.245401   .2258436    -5.51   0.000    -1.688046   -.8027554
                               UT  |  -.3692784     .20978    -1.76   0.078    -.7804396    .0418828
                               VT  |  -.0581917   .2315461    -0.25   0.802    -.5120136    .3956303
                               VA  |  -.7031821   .2705374    -2.60   0.009    -1.233426   -.1729386
                               WA  |  -.9891452   .2215726    -4.46   0.000     -1.42342   -.5548709
                               WV  |  -.4904082   .2651731    -1.85   0.064    -1.010138    .0293216
                               WI  |  -.5345467   .2221096    -2.41   0.016    -.9698736   -.0992198
                               WY  |   .1794183   .2104176     0.85   0.394    -.2329926    .5918291
                                   |
                              year |
                             1984  |   .0662276   .0898342     0.74   0.461    -.1098441    .2422993
                             1988  |   .1299014   .0872908     1.49   0.137    -.0411855    .3009882
                             1994  |    .022564   .0927151     0.24   0.808    -.1591542    .2042823
                             1998  |  -.1963388    .098583    -1.99   0.046    -.3895579   -.0031197
                             2004  |  -.2686975   .1042481    -2.58   0.010    -.4730201   -.0643749
                             2008  |  -.2719732   .1206671    -2.25   0.024    -.5084764     -.03547
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -3.389471   .6580864                     -4.679296   -2.099645
                             /cut2 |  -.3819122    .650125                     -1.656134    .8923093
                             /cut3 |   .9030895   .6498919                     -.3706752    2.176854
                             /cut4 |   2.909541   .6519057                      1.631829    4.187253
----------------------------------------------------------------------------------------------------

. est sto a2

. 
. ologit reve_1c b1.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_emplo
> y_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.ye
> ar , r 

Iteration 0:   log pseudolikelihood = -10351.868  
Iteration 1:   log pseudolikelihood = -9378.5499  
Iteration 2:   log pseudolikelihood =  -9360.604  
Iteration 3:   log pseudolikelihood = -9360.5601  
Iteration 4:   log pseudolikelihood = -9360.5601  

Ordered logistic regression                     Number of obs     =      7,543
                                                Wald chi2(93)     =    1799.99
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -9360.5601               Pseudo R2         =     0.0958

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1c |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                        White Man  |   .1532275   .0659598     2.32   0.020     .0239486    .2825063
                     Man of Color  |  -.3785118   .1120691    -3.38   0.001    -.5981632   -.1588604
                   Woman of Color  |  -.4817073   .1875216    -2.57   0.010    -.8492428   -.1141718
                                   |
                     civil_service |
                              Yes  |  -.4786386    .055548    -8.62   0.000    -.5875107   -.3697665
                      weekly_hours |   .0395543   .0029311    13.49   0.000     .0338095    .0452991
                               age |  -.0155138   .0219281    -0.71   0.479     -.058492    .0274645
                             age_2 |   6.43e-06   .0002187     0.03   0.977    -.0004222    .0004351
                                   |
                               edu |
              High school or less  |   .0429885   .2095777     0.21   0.837    -.3677762    .4537532
                     Some college  |  -.1672944   .1075566    -1.56   0.120    -.3781014    .0435126
                   Graduate study  |   .1129532   .0758331     1.49   0.136    -.0356769    .2615833
                  Graduate degree  |   .0497169    .060836     0.82   0.414    -.0695195    .1689534
                                   |
                years_employ_state |   .0049376    .003876     1.27   0.203    -.0026593    .0125345
               years_employ_agency |  -.0098846   .0041501    -2.38   0.017    -.0180186   -.0017505
             years_employ_position |   .0077178   .0053947     1.43   0.153    -.0028557    .0182912
                                   |
                              pid5 |
                       Republican  |   .2280009   .0778427     2.93   0.003      .075432    .3805697
                  Lean Republican  |  -.0335429   .0991719    -0.34   0.735    -.2279163    .1608306
                  Lean Democratic  |   -.002536   .0930573    -0.03   0.978     -.184925     .179853
                       Democratic  |   .1816716   .0728001     2.50   0.013      .038986    .3243572
                                   |
                       agency_size |
                           25-100  |   .2577081   .0703178     3.66   0.000     .1198877    .3955285
                          101-500  |   .4706283   .0811016     5.80   0.000      .311672    .6295846
                        501-1,000  |   .5575088   .1073675     5.19   0.000     .3470723    .7679452
                      1,001-5,000  |   .6310467   .1140187     5.53   0.000     .4075741    .8545194
                       Over 5,000  |   .8554307   .1566426     5.46   0.000     .5484169    1.162444
                                   |
                 log_agency_budget |   .1545551   .0190955     8.09   0.000     .1171286    .1919815
                      inst6017_nom |   .0036019   .0026201     1.37   0.169    -.0015333    .0087371
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.7217645   .1543915    -4.67   0.000    -1.024366   -.4191628
                Staff: Non-Fiscal  |  -1.344385   .1442132    -9.32   0.000    -1.627038   -1.061732
Income Security & Social Services  |  -1.544121   .1327481   -11.63   0.000    -1.804302   -1.283939
                        Education  |  -1.333907   .1431981    -9.32   0.000     -1.61457   -1.053244
                           Health  |  -1.444351    .138387   -10.44   0.000    -1.715585   -1.173118
                Natural Resources  |  -.9783398   .1251478    -7.82   0.000    -1.223625   -.7330546
             Environment & Energy  |  -1.157852   .1281523    -9.03   0.000    -1.409025   -.9066778
             Economic Development  |  -1.169661   .1311787    -8.92   0.000    -1.426767   -.9125557
                 Criminal Justice  |  -1.490325   .1327232   -11.23   0.000    -1.750458   -1.230192
                       Regulatory  |  -1.341997   .1238209   -10.84   0.000    -1.584681   -1.099312
                   Transportation  |   -.921331   .1483283    -6.21   0.000    -1.212049   -.6306128
                            Other  |  -1.484794   .1321397   -11.24   0.000    -1.743783   -1.225804
                                   |
                             state |
                               AK  |   .1844862   .2185489     0.84   0.399    -.2438617    .6128342
                               AZ  |   .0686257   .2388438     0.29   0.774    -.3994995    .5367509
                               AR  |   .5962324   .2429482     2.45   0.014     .1200627    1.072402
                               CA  |  -.0899827   .2443573    -0.37   0.713    -.5689141    .3889488
                               CO  |   .3909344   .2112609     1.85   0.064    -.0231294    .8049982
                               CT  |   .1792289   .2429228     0.74   0.461    -.2968911    .6553489
                               DE  |   .1713338   .2274411     0.75   0.451    -.2744427    .6171102
                               FL  |  -.5273958   .2248197    -2.35   0.019    -.9680344   -.0867573
                               GA  |   .3733606   .2261473     1.65   0.099      -.06988    .8166013
                               HI  |  -.4723271   .2657496    -1.78   0.076    -.9931867    .0485325
                               ID  |  -.0087548   .2270013    -0.04   0.969    -.4536692    .4361596
                               IL  |   .1443683   .2490528     0.58   0.562    -.3437662    .6325027
                               IN  |  -.2772225   .2239881    -1.24   0.216    -.7162311    .1617862
                               IA  |  -.0552067   .2152792    -0.26   0.798    -.4771462    .3667327
                               KS  |   .5429078   .2175227     2.50   0.013     .1165712    .9692445
                               KY  |   -.493915   .2355542    -2.10   0.036    -.9555926   -.0322373
                               LA  |   .6365047   .2605336     2.44   0.015     .1258682    1.147141
                               ME  |   .8528493   .2276178     3.75   0.000     .4067265    1.298972
                               MD  |   .2340007    .218611     1.07   0.284     -.194469    .6624704
                               MA  |    .473201   .2536004     1.87   0.062    -.0238466    .9702486
                               MI  |   .8221413   .2281193     3.60   0.000     .3750357    1.269247
                               MN  |   .3196358   .2101994     1.52   0.128    -.0923475     .731619
                               MS  |   .3302594    .238284     1.39   0.166    -.1367686    .7972874
                               MO  |   .3331271   .2166495     1.54   0.124    -.0914981    .7577523
                               MT  |  -.2830532   .2152178    -1.32   0.188    -.7048723    .1387659
                               NE  |  -.0741863    .218658    -0.34   0.734    -.5027482    .3543756
                               NV  |  -.7577281   .2102203    -3.60   0.000    -1.169752   -.3457039
                               NH  |   1.064797   .2139455     4.98   0.000     .6454716    1.484122
                               NJ  |  -.4378222   .2409223    -1.82   0.069    -.9100212    .0343767
                               NM  |  -.4457853   .2325061    -1.92   0.055    -.9014888    .0099182
                               NY  |  -.5236403    .270506    -1.94   0.053    -1.053822    .0065417
                               NC  |  -.1303479   .2013047    -0.65   0.517    -.5248978     .264202
                               ND  |  -.3949463   .2050011    -1.93   0.054    -.7967411    .0068485
                               OH  |  -.3798706   .2215315    -1.71   0.086    -.8140643    .0543231
                               OK  |    .767976    .230308     3.33   0.001     .3165807    1.219371
                               OR  |  -.2785938   .2128417    -1.31   0.191    -.6957559    .1385682
                               PA  |   .1065086   .2358795     0.45   0.652    -.3558068     .568824
                               RI  |  -.0517783   .2449748    -0.21   0.833    -.5319201    .4283636
                               SC  |   1.077082   .2380934     4.52   0.000     .6104275    1.543737
                               SD  |  -.8420329   .2224203    -3.79   0.000    -1.277969   -.4060971
                               TN  |   .0646205   .2385057     0.27   0.786    -.4028422    .5320831
                               TX  |  -.0094745   .2401865    -0.04   0.969    -.4802313    .4612823
                               UT  |  -.5591416   .2109727    -2.65   0.008    -.9726406   -.1456426
                               VT  |   .7496343   .2296456     3.26   0.001     .2995372    1.199731
                               VA  |  -.3137102   .2323159    -1.35   0.177    -.7690411    .1416206
                               WA  |  -.4032374   .2156546    -1.87   0.062    -.8259127    .0194378
                               WV  |  -.3648495   .2244198    -1.63   0.104    -.8047042    .0750051
                               WI  |   .2197584   .2066504     1.06   0.288     -.185269    .6247858
                               WY  |  -.7727914   .2178966    -3.55   0.000    -1.199861    -.345722
                                   |
                              year |
                             1978  |  -.5116036   .0906929    -5.64   0.000    -.6893584   -.3338489
                             1984  |   -.507846   .0878024    -5.78   0.000    -.6799355   -.3357565
                             1988  |  -.4688999   .0825201    -5.68   0.000    -.6306362   -.3071635
                             1994  |   -.466606     .08734    -5.34   0.000    -.6377892   -.2954228
                             1998  |  -.7226027   .0893663    -8.09   0.000    -.8977575    -.547448
                             2004  |  -.9583222   .0939958   -10.20   0.000    -1.142551   -.7740937
                             2008  |   -.933202   .1098137    -8.50   0.000    -1.148433   -.7179711
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -4.021636    .618503                     -5.233879   -2.809392
                             /cut2 |  -.3408137   .6073041                     -1.531108    .8494806
                             /cut3 |   1.141539   .6074302                     -.0490024     2.33208
                             /cut4 |   3.294912   .6083821                      2.102505     4.48732
----------------------------------------------------------------------------------------------------

. est sto a3

. 
. ologit reve_1d b1.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_emplo
> y_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.ye
> ar , r 

Iteration 0:   log pseudolikelihood = -8728.3519  
Iteration 1:   log pseudolikelihood = -8200.6981  
Iteration 2:   log pseudolikelihood = -8194.7582  
Iteration 3:   log pseudolikelihood = -8194.7467  
Iteration 4:   log pseudolikelihood = -8194.7467  

Ordered logistic regression                     Number of obs     =      6,340
                                                Wald chi2(92)     =     999.27
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -8194.7467               Pseudo R2         =     0.0611

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                        White Man  |   .0915631   .0685134     1.34   0.181    -.0427207    .2258469
                     Man of Color  |  -.1655842   .1146206    -1.44   0.149    -.3902364    .0590679
                   Woman of Color  |   -.515073   .2119503    -2.43   0.015    -.9304879    -.099658
                                   |
                     civil_service |
                              Yes  |  -.2674122   .0601311    -4.45   0.000    -.3852671   -.1495573
                      weekly_hours |   .0295276   .0031084     9.50   0.000     .0234353    .0356198
                               age |  -.0403184   .0252539    -1.60   0.110    -.0898151    .0091784
                             age_2 |   .0002548   .0002524     1.01   0.313    -.0002398    .0007494
                                   |
                               edu |
              High school or less  |   .0765339   .2636174     0.29   0.772    -.4401468    .5932146
                     Some college  |  -.0604091   .1194484    -0.51   0.613    -.2945238    .1737055
                   Graduate study  |   .1352846    .082029     1.65   0.099    -.0254892    .2960584
                  Graduate degree  |   .0574484   .0656242     0.88   0.381    -.0711726    .1860694
                                   |
                years_employ_state |   .0120718   .0040276     3.00   0.003      .004178    .0199657
               years_employ_agency |  -.0078704   .0043119    -1.83   0.068    -.0163215    .0005807
             years_employ_position |    .004455   .0056835     0.78   0.433    -.0066844    .0155945
                                   |
                              pid5 |
                       Republican  |   .0864186    .082324     1.05   0.294    -.0749334    .2477706
                  Lean Republican  |   .0044505   .1093365     0.04   0.968    -.2098452    .2187461
                  Lean Democratic  |  -.0091306   .1026936    -0.09   0.929    -.2104064    .1921451
                       Democratic  |   .0612516    .076418     0.80   0.423    -.0885249    .2110281
                                   |
                       agency_size |
                           25-100  |   .0577822   .0742731     0.78   0.437    -.0877903    .2033547
                          101-500  |   .0949199   .0847446     1.12   0.263    -.0711766    .2610163
                        501-1,000  |   .1025891   .1174273     0.87   0.382    -.1275642    .3327423
                      1,001-5,000  |  -.0089695   .1225841    -0.07   0.942    -.2492299    .2312908
                       Over 5,000  |   .2036781    .166484     1.22   0.221    -.1226246    .5299808
                                   |
                 log_agency_budget |   .0999747   .0206675     4.84   0.000     .0594671    .1404823
                      inst6017_nom |   .0060982   .0029472     2.07   0.039     .0003217    .0118747
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.1229972   .1637844    -0.75   0.453    -.4440087    .1980144
                Staff: Non-Fiscal  |  -.8768568   .1644321    -5.33   0.000    -1.199138   -.5545758
Income Security & Social Services  |  -.9503731   .1509034    -6.30   0.000    -1.246138    -.654608
                        Education  |  -.6935631   .1615647    -4.29   0.000    -1.010224    -.376902
                           Health  |  -.9182932   .1576484    -5.82   0.000    -1.227278    -.609308
                Natural Resources  |  -.9120763   .1430177    -6.38   0.000    -1.192386   -.6317669
             Environment & Energy  |  -1.032433   .1439321    -7.17   0.000    -1.314535   -.7503316
             Economic Development  |  -1.134385    .147684    -7.68   0.000     -1.42384   -.8449294
                 Criminal Justice  |  -.9563278   .1512715    -6.32   0.000    -1.252815    -.659841
                       Regulatory  |  -1.162944   .1406683    -8.27   0.000    -1.438649   -.8872391
                   Transportation  |  -.8374815   .1672608    -5.01   0.000    -1.165307   -.5096564
                            Other  |  -.9052627   .1495118    -6.05   0.000      -1.1983    -.612225
                                   |
                             state |
                               AK  |   1.399893   .2527265     5.54   0.000     .9045582    1.895228
                               AZ  |   .9238635   .2647702     3.49   0.000     .4049235    1.442804
                               AR  |   .7222201   .2597652     2.78   0.005     .2130896    1.231351
                               CA  |   1.040541   .2968631     3.51   0.000     .4586997    1.622382
                               CO  |   .7062144   .2520423     2.80   0.005     .2122207    1.200208
                               CT  |     .54922   .2832048     1.94   0.052    -.0058512    1.104291
                               DE  |   .0967001   .2752153     0.35   0.725    -.4427119    .6361121
                               FL  |    .917924   .2599173     3.53   0.000     .4084954    1.427353
                               GA  |   .4995448   .2725782     1.83   0.067    -.0346986    1.033788
                               HI  |   -.098179   .2951121    -0.33   0.739    -.6765881    .4802301
                               ID  |   .5452425   .2527906     2.16   0.031      .049782    1.040703
                               IL  |   .5357001   .2844619     1.88   0.060     -.021835    1.093235
                               IN  |   .1926003   .2668031     0.72   0.470    -.3303242    .7155247
                               IA  |   .4623393   .2506624     1.84   0.065      -.02895    .9536285
                               KS  |   1.192527    .257752     4.63   0.000     .6873425    1.697712
                               KY  |   .6270707   .2615218     2.40   0.016     .1144974    1.139644
                               LA  |   .8133197   .2889778     2.81   0.005     .2469336    1.379706
                               ME  |   .8874817   .2850533     3.11   0.002     .3287874    1.446176
                               MD  |   .8027602   .2583373     3.11   0.002     .2964284    1.309092
                               MA  |   .8799829   .2921223     3.01   0.003     .3074338    1.452532
                               MI  |   1.697745   .2692553     6.31   0.000     1.170015    2.225476
                               MN  |   1.185779    .249503     4.75   0.000     .6967623    1.674796
                               MS  |   .4389355   .2610983     1.68   0.093    -.0728077    .9506787
                               MO  |   .7516882   .2590888     2.90   0.004     .2438835    1.259493
                               MT  |   .4021156   .2465757     1.63   0.103    -.0811638    .8853951
                               NE  |   .9359898   .2584906     3.62   0.000     .4293575    1.442622
                               NV  |   .4210234   .2464239     1.71   0.088    -.0619585    .9040053
                               NH  |    .861979   .2763309     3.12   0.002     .3203805    1.403578
                               NJ  |   .3240292   .2653246     1.22   0.222    -.1959976    .8440559
                               NM  |    .450611   .2702053     1.67   0.095    -.0789816    .9802036
                               NY  |   .3916939   .3532072     1.11   0.267    -.3005795    1.083967
                               NC  |   .3156418   .2418451     1.31   0.192    -.1583658    .7896494
                               ND  |  -.6404053   .2569048    -2.49   0.013    -1.143929   -.1368812
                               OH  |   .5187461   .2821676     1.84   0.066    -.0342923    1.071784
                               OK  |   1.100864   .2567021     4.29   0.000      .597737    1.603991
                               OR  |   .6240373   .2571202     2.43   0.015     .1200909    1.127984
                               PA  |   1.029567   .2757739     3.73   0.000     .4890604    1.570074
                               RI  |  -.2562584   .2859077    -0.90   0.370    -.8166271    .3041104
                               SC  |   1.400709   .2775545     5.05   0.000     .8567119    1.944705
                               SD  |  -.2997918   .2582692    -1.16   0.246    -.8059901    .2064065
                               TN  |   .5386902   .2678191     2.01   0.044     .0137745    1.063606
                               TX  |   1.567741   .2655896     5.90   0.000     1.047195    2.088287
                               UT  |   .5426185   .2399215     2.26   0.024     .0723809    1.012856
                               VT  |   .2893295   .2762285     1.05   0.295    -.2520685    .8307275
                               VA  |   .3164445   .2611018     1.21   0.226    -.1953056    .8281945
                               WA  |   .6177409   .2398288     2.58   0.010     .1476851    1.087797
                               WV  |   .1170794   .2607521     0.45   0.653    -.3939852    .6281441
                               WI  |   1.243647   .2552009     4.87   0.000     .7434623    1.743831
                               WY  |  -.2981704   .2535781    -1.18   0.240    -.7951743    .1988335
                                   |
                              year |
                             1984  |  -.0881298   .0899369    -0.98   0.327     -.264403    .0881433
                             1988  |    .154664   .0867667     1.78   0.075    -.0153957    .3247236
                             1994  |   .2173252   .0923942     2.35   0.019     .0362359    .3984145
                             1998  |  -.0626998   .0978743    -0.64   0.522    -.2545298    .1291302
                             2004  |  -.4073416   .1006214    -4.05   0.000    -.6045558   -.2101273
                             2008  |  -.1814891   .1131612    -1.60   0.109    -.4032808    .0403027
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -3.176165   .6990784                     -4.546333   -1.805997
                             /cut2 |  -.1177411   .6925692                     -1.475152     1.23967
                             /cut3 |   1.306416   .6928622                     -.0515684    2.664401
                             /cut4 |   3.470867    .694034                      2.110586    4.831149
----------------------------------------------------------------------------------------------------

. est sto a4

. 
. 
. est restore a1
(results a1 are active now)

. margins, dydx(3.intersection)

Average marginal effects                        Number of obs     =      7,515
Model VCE    : Robust

dy/dx w.r.t. : 3.intersection
1._predict   : Pr(reve_1a==1), predict(pr outcome(1))
2._predict   : Pr(reve_1a==2), predict(pr outcome(2))
3._predict   : Pr(reve_1a==3), predict(pr outcome(3))
4._predict   : Pr(reve_1a==4), predict(pr outcome(4))
5._predict   : Pr(reve_1a==5), predict(pr outcome(5))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
1.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |   .0374422   .0240954     1.55   0.120    -.0097838    .0846682
             2  |   .0099144   .0047849     2.07   0.038     .0005361    .0192926
             3  |  -.0192757   .0122152    -1.58   0.115     -.043217    .0046657
             4  |  -.0233816   .0138106    -1.69   0.090    -.0504499    .0036867
             5  |  -.0046993   .0026736    -1.76   0.079    -.0099395    .0005409
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est restore a2
(results a2 are active now)

. margins, dydx(3.intersection)

Average marginal effects                        Number of obs     =      6,378
Model VCE    : Robust

dy/dx w.r.t. : 3.intersection
1._predict   : Pr(reve_1b==1), predict(pr outcome(1))
2._predict   : Pr(reve_1b==2), predict(pr outcome(2))
3._predict   : Pr(reve_1b==3), predict(pr outcome(3))
4._predict   : Pr(reve_1b==4), predict(pr outcome(4))
5._predict   : Pr(reve_1b==5), predict(pr outcome(5))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
1.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |   .0112888   .0060312     1.87   0.061    -.0005322    .0231097
             2  |   .0525471   .0249132     2.11   0.035      .003718    .1013761
             3  |   .0067543    .002109     3.20   0.001     .0026208    .0108878
             4  |  -.0333506    .016522    -2.02   0.044    -.0657331    -.000968
             5  |  -.0372396   .0161196    -2.31   0.021    -.0688334   -.0056457
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est restore a3
(results a3 are active now)

. margins, dydx(3.intersection)

Average marginal effects                        Number of obs     =      7,543
Model VCE    : Robust

dy/dx w.r.t. : 3.intersection
1._predict   : Pr(reve_1c==1), predict(pr outcome(1))
2._predict   : Pr(reve_1c==2), predict(pr outcome(2))
3._predict   : Pr(reve_1c==3), predict(pr outcome(3))
4._predict   : Pr(reve_1c==4), predict(pr outcome(4))
5._predict   : Pr(reve_1c==5), predict(pr outcome(5))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
1.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |    .007918   .0037737     2.10   0.036     .0005218    .0153142
             2  |   .0816046   .0326783     2.50   0.013     .0175563    .1456529
             3  |   .0034624   .0028685     1.21   0.227    -.0021599    .0090846
             4  |   -.059365   .0233305    -2.54   0.011     -.105092    -.013638
             5  |    -.03362   .0114555    -2.93   0.003    -.0560723   -.0111676
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est restore a4
(results a4 are active now)

. margins, dydx(3.intersection)

Average marginal effects                        Number of obs     =      6,340
Model VCE    : Robust

dy/dx w.r.t. : 3.intersection
1._predict   : Pr(reve_1d==1), predict(pr outcome(1))
2._predict   : Pr(reve_1d==2), predict(pr outcome(2))
3._predict   : Pr(reve_1d==3), predict(pr outcome(3))
4._predict   : Pr(reve_1d==4), predict(pr outcome(4))
5._predict   : Pr(reve_1d==5), predict(pr outcome(5))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
1.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |   .0159293   .0080371     1.98   0.047     .0001769    .0316817
             2  |    .089763    .037316     2.41   0.016     .0166251    .1629009
             3  |  -.0049413   .0071346    -0.69   0.489     -.018925    .0090423
             4  |  -.0716996   .0287586    -2.49   0.013    -.1280653   -.0153338
             5  |  -.0290514   .0101575    -2.86   0.004    -.0489597   -.0091431
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. 
. **** RESULTS EXPORTED AND FORMATTED IN EXCEL ****
. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B2 ******
. ologit reve_1a b2.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_emplo
> y_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.ye
> ar , r 

Iteration 0:   log pseudolikelihood = -10356.699  
Iteration 1:   log pseudolikelihood = -8819.4854  
Iteration 2:   log pseudolikelihood = -8749.2319  
Iteration 3:   log pseudolikelihood = -8749.0873  
Iteration 4:   log pseudolikelihood = -8749.0873  

Ordered logistic regression                     Number of obs     =      7,515
                                                Wald chi2(93)     =    2873.27
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -8749.0873               Pseudo R2         =     0.1552

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                        White Man  |   .1357595   .1014439     1.34   0.181    -.0630669    .3345859
                      White Woman  |  -.1064623   .1157943    -0.92   0.358     -.333415    .1204905
                   Woman of Color  |  -.3916535   .1892528    -2.07   0.039    -.7625821   -.0207248
                                   |
                     civil_service |
                              Yes  |   -.971733   .0600389   -16.19   0.000    -1.089407   -.8540589
                      weekly_hours |   .0521346   .0031106    16.76   0.000     .0460381    .0582312
                               age |  -.0374195   .0224833    -1.66   0.096    -.0814859    .0066468
                             age_2 |     .00053   .0002215     2.39   0.017     .0000957    .0009642
                                   |
                               edu |
              High school or less  |   .0306371   .1979765     0.15   0.877    -.3573896    .4186638
                     Some college  |   .1162062   .1062374     1.09   0.274    -.0920154    .3244277
                   Graduate study  |   .0538401    .077269     0.70   0.486    -.0976045    .2052846
                  Graduate degree  |  -.0971884   .0647571    -1.50   0.133    -.2241101    .0297332
                                   |
                years_employ_state |   -.000374   .0041522    -0.09   0.928    -.0085121    .0077642
               years_employ_agency |  -.0313019    .004373    -7.16   0.000    -.0398728    -.022731
             years_employ_position |   .0076163   .0054818     1.39   0.165    -.0031279    .0183605
                                   |
                              pid5 |
                       Republican  |    .481098   .0819153     5.87   0.000     .3205471     .641649
                  Lean Republican  |   .1207507   .1017217     1.19   0.235    -.0786201    .3201215
                  Lean Democratic  |  -.0231355   .0978389    -0.24   0.813    -.2148963    .1686252
                       Democratic  |    .473495   .0747023     6.34   0.000     .3270812    .6199088
                                   |
                       agency_size |
                           25-100  |   .1619845   .0731383     2.21   0.027     .0186361    .3053329
                          101-500  |   .5105166   .0842327     6.06   0.000     .3454235    .6756097
                        501-1,000  |   .7649114   .1109232     6.90   0.000     .5475059    .9823169
                      1,001-5,000  |   1.068553   .1151358     9.28   0.000     .8428913    1.294215
                       Over 5,000  |   1.494491   .1556228     9.60   0.000     1.189476    1.799506
                                   |
                 log_agency_budget |   .1757835   .0201581     8.72   0.000     .1362744    .2152926
                      inst6017_nom |  -.0030011   .0028368    -1.06   0.290    -.0085611     .002559
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .6925461   .1617936     4.28   0.000     .3754364    1.009656
                Staff: Non-Fiscal  |  -.2202206    .157977    -1.39   0.163    -.5298497    .0894086
Income Security & Social Services  |   -1.47653    .136935   -10.78   0.000    -1.744918   -1.208143
                        Education  |  -.9776317   .1461753    -6.69   0.000     -1.26413   -.6911333
                           Health  |  -1.648944   .1473031   -11.19   0.000    -1.937653   -1.360235
                Natural Resources  |  -.7923242   .1261825    -6.28   0.000    -1.039637   -.5450112
             Environment & Energy  |  -.7873803   .1351057    -5.83   0.000    -1.052183   -.5225781
             Economic Development  |   .0223083   .1390922     0.16   0.873    -.2503073     .294924
                 Criminal Justice  |  -.9552778   .1347269    -7.09   0.000    -1.219338   -.6912179
                       Regulatory  |  -1.257715   .1303817    -9.65   0.000    -1.513259   -1.002172
                   Transportation  |    -1.0062   .1410028    -7.14   0.000    -1.282561     -.72984
                            Other  |   -.757503    .137055    -5.53   0.000    -1.026126   -.4888801
                                   |
                             state |
                               AK  |  -.3341416   .2197752    -1.52   0.128    -.7648931    .0966098
                               AZ  |  -1.072071   .2452188    -4.37   0.000    -1.552691   -.5914514
                               AR  |  -.2319074   .2038058    -1.14   0.255    -.6313594    .1675447
                               CA  |  -2.499601   .2436337   -10.26   0.000    -2.977114   -2.022088
                               CO  |  -.0331212   .2128896    -0.16   0.876    -.4503771    .3841348
                               CT  |  -1.157115   .2515839    -4.60   0.000     -1.65021   -.6640194
                               DE  |   -.367357   .2112314    -1.74   0.082     -.781363    .0466489
                               FL  |  -1.685318   .2436817    -6.92   0.000    -2.162925   -1.207711
                               GA  |  -.9216965   .2307668    -3.99   0.000    -1.373991   -.4694019
                               HI  |  -.7774421   .2439012    -3.19   0.001     -1.25548   -.2994046
                               ID  |   .2447971   .2047634     1.20   0.232    -.1565316    .6461259
                               IL  |  -1.432487   .2441575    -5.87   0.000    -1.911027   -.9539475
                               IN  |  -.5692946    .230641    -2.47   0.014    -1.021343   -.1172465
                               IA  |  -.2820726   .1985466    -1.42   0.155    -.6712168    .1070717
                               KS  |  -.4032152    .227537    -1.77   0.076    -.8491795    .0427492
                               KY  |  -1.063754   .2289834    -4.65   0.000    -1.512553   -.6149547
                               LA  |  -.8155946   .2608939    -3.13   0.002    -1.326937   -.3042519
                               ME  |  -.0783662   .2253939    -0.35   0.728    -.5201302    .3633978
                               MD  |  -.9876069   .2317822    -4.26   0.000    -1.441892   -.5333221
                               MA  |  -1.693045   .2448103    -6.92   0.000    -2.172865   -1.213226
                               MI  |   -.874717     .21754    -4.02   0.000    -1.301088   -.4483464
                               MN  |  -1.107307   .2253961    -4.91   0.000    -1.549075   -.6655391
                               MS  |  -.2822958   .2248794    -1.26   0.209    -.7230512    .1584597
                               MO  |  -1.220202   .2130826    -5.73   0.000    -1.637836   -.8025675
                               MT  |   .1358397   .2015739     0.67   0.500    -.2592379    .5309173
                               NE  |   .1869023   .2290752     0.82   0.415     -.262077    .6358815
                               NV  |  -.2360691   .2123013    -1.11   0.266     -.652172    .1800339
                               NH  |  -.0685534   .2225901    -0.31   0.758    -.5048219    .3677151
                               NJ  |  -1.228063   .2328847    -5.27   0.000    -1.684509   -.7716174
                               NM  |   .0465281   .2273325     0.20   0.838    -.3990354    .4920916
                               NY  |  -2.188579   .2690821    -8.13   0.000    -2.715971   -1.661188
                               NC  |  -1.032744   .1957113    -5.28   0.000    -1.416331   -.6491567
                               ND  |   .6604772    .205922     3.21   0.001     .2568774    1.064077
                               OH  |  -1.235707   .2358003    -5.24   0.000    -1.697867   -.7735465
                               OK  |  -.6671675   .2154399    -3.10   0.002    -1.089422   -.2449129
                               OR  |  -.2735063   .2181166    -1.25   0.210     -.701007    .1539945
                               PA  |  -1.880874   .2278246    -8.26   0.000    -2.327402   -1.434346
                               RI  |   .2145086    .226937     0.95   0.345    -.2302797    .6592969
                               SC  |  -.5503567   .2137538    -2.57   0.010    -.9693065   -.1314069
                               SD  |   .3450091   .2136162     1.62   0.106     -.073671    .7636891
                               TN  |  -1.180326   .2327253    -5.07   0.000    -1.636459   -.7241927
                               TX  |  -1.979577   .2153058    -9.19   0.000    -2.401568   -1.557585
                               UT  |   .0487906   .2036328     0.24   0.811    -.3503224    .4479036
                               VT  |    .260382   .2111284     1.23   0.217    -.1534221     .674186
                               VA  |  -1.115041   .2323401    -4.80   0.000    -1.570419   -.6596628
                               WA  |  -.9946893   .2303605    -4.32   0.000    -1.446187   -.5431911
                               WV  |  -.5057771   .2176936    -2.32   0.020    -.9324488   -.0791055
                               WI  |  -.4418259   .2162913    -2.04   0.041    -.8657491   -.0179028
                               WY  |   .5443989   .1957128     2.78   0.005     .1608089    .9279889
                                   |
                              year |
                             1978  |  -.6629782    .087449    -7.58   0.000    -.8343751   -.4915813
                             1984  |   -.673541   .0838074    -8.04   0.000    -.8378006   -.5092815
                             1988  |  -.9775924   .0794303   -12.31   0.000    -1.133273   -.8219118
                             1994  |  -.8358436   .0852362    -9.81   0.000    -1.002904   -.6687837
                             1998  |  -1.171177   .0918104   -12.76   0.000    -1.351122    -.991232
                             2004  |  -1.224451    .095131   -12.87   0.000    -1.410904   -1.037997
                             2008  |  -1.507369   .1216842   -12.39   0.000    -1.745865   -1.268872
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.369635   .6300733                     -2.604556   -.1347143
                             /cut2 |   1.272976   .6297272                      .0387331    2.507218
                             /cut3 |   2.750027   .6310779                      1.513137    3.986917
                             /cut4 |   5.265766   .6394459                      4.012475    6.519057
----------------------------------------------------------------------------------------------------

. est sto a5

. 
. ologit reve_1b b2.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_emplo
> y_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.ye
> ar , r 

Iteration 0:   log pseudolikelihood = -9204.7672  
Iteration 1:   log pseudolikelihood = -8101.5966  
Iteration 2:   log pseudolikelihood = -8073.7021  
Iteration 3:   log pseudolikelihood = -8073.6594  
Iteration 4:   log pseudolikelihood = -8073.6594  

Ordered logistic regression                     Number of obs     =      6,378
                                                Wald chi2(92)     =    2018.62
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -8073.6594               Pseudo R2         =     0.1229

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1b |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                        White Man  |   .0567718    .103254     0.55   0.582    -.1456023    .2591459
                      White Woman  |  -.0934381   .1140126    -0.82   0.412    -.3168987    .1300225
                   Woman of Color  |   -.465631   .1869961    -2.49   0.013    -.8321367   -.0991253
                                   |
                     civil_service |
                              Yes  |  -.8010587   .0607996   -13.18   0.000    -.9202237   -.6818938
                      weekly_hours |   .0479222   .0033269    14.40   0.000     .0414016    .0544429
                               age |  -.0767768   .0231595    -3.32   0.001    -.1221687   -.0313849
                             age_2 |   .0007002   .0002276     3.08   0.002     .0002542    .0011462
                                   |
                               edu |
              High school or less  |   .2658405   .2268917     1.17   0.241     -.178859    .7105401
                     Some college  |   .1530398   .1191205     1.28   0.199    -.0804321    .3865117
                   Graduate study  |   .1476438   .0824394     1.79   0.073    -.0139344     .309222
                  Graduate degree  |   .0734268   .0687729     1.07   0.286    -.0613655    .2082192
                                   |
                years_employ_state |   .0056667   .0042638     1.33   0.184    -.0026902    .0140235
               years_employ_agency |  -.0282912   .0044624    -6.34   0.000    -.0370375    -.019545
             years_employ_position |  -.0066664    .005934    -1.12   0.261    -.0182968     .004964
                                   |
                              pid5 |
                       Republican  |   .3837354   .0851776     4.51   0.000     .2167903    .5506805
                  Lean Republican  |   .0228367   .1080157     0.21   0.833    -.1888702    .2345436
                  Lean Democratic  |  -.0635507   .0975554    -0.65   0.515    -.2547557    .1276544
                       Democratic  |   .3259516   .0797447     4.09   0.000      .169655    .4822483
                                   |
                       agency_size |
                           25-100  |  -.0445093   .0785051    -0.57   0.571    -.1983765     .109358
                          101-500  |   .1968848   .0895371     2.20   0.028     .0213954    .3723743
                        501-1,000  |   .3376189   .1193704     2.83   0.005     .1036573    .5715805
                      1,001-5,000  |   .6280194   .1251758     5.02   0.000     .3826794    .8733594
                       Over 5,000  |   1.022571   .1730498     5.91   0.000     .6833995    1.361742
                                   |
                 log_agency_budget |   .1899252   .0216562     8.77   0.000     .1474799    .2323705
                      inst6017_nom |   .0028871   .0031288     0.92   0.356    -.0032452    .0090195
                                   |
                          funcat13 |
                    Staff: Fiscal  |   1.405647   .1764997     7.96   0.000     1.059714     1.75158
                Staff: Non-Fiscal  |   .9466027    .184014     5.14   0.000     .5859419    1.307263
Income Security & Social Services  |  -.4537725   .1521941    -2.98   0.003    -.7520675   -.1554774
                        Education  |  -.4254235   .1625536    -2.62   0.009    -.7440227   -.1068244
                           Health  |  -.6096505   .1594823    -3.82   0.000    -.9222301   -.2970709
                Natural Resources  |  -.0851974   .1438454    -0.59   0.554    -.3671291    .1967344
             Environment & Energy  |   .0260771   .1494181     0.17   0.861    -.2667771    .3189312
             Economic Development  |   .7596595   .1528347     4.97   0.000     .4601089     1.05921
                 Criminal Justice  |   .0158167    .152794     0.10   0.918     -.283654    .3152875
                       Regulatory  |  -.6198936   .1436041    -4.32   0.000    -.9013524   -.3384348
                   Transportation  |  -.2217456   .1602336    -1.38   0.166    -.5357977    .0923064
                            Other  |   .1386793   .1519915     0.91   0.362    -.1592186    .4365771
                                   |
                             state |
                               AK  |  -.0763772   .2326042    -0.33   0.743     -.532273    .3795186
                               AZ  |  -.3752213   .2390634    -1.57   0.117     -.843777    .0933344
                               AR  |   .3394096   .2251537     1.51   0.132    -.1018836    .7807027
                               CA  |  -1.533002   .2558924    -5.99   0.000    -2.034542   -1.031462
                               CO  |  -.2716633   .2251548    -1.21   0.228    -.7129587     .169632
                               CT  |  -.8201582   .2658149    -3.09   0.002    -1.341146   -.2991707
                               DE  |   -.853052   .2246583    -3.80   0.000    -1.293374   -.4127299
                               FL  |  -1.320788   .2392821    -5.52   0.000    -1.789772   -.8518035
                               GA  |  -.8142959   .2564716    -3.17   0.001    -1.316971   -.3116208
                               HI  |  -1.396295    .267658    -5.22   0.000    -1.920895   -.8716948
                               ID  |    .726494   .2240838     3.24   0.001     .2872977     1.16569
                               IL  |  -.3944151   .2884722    -1.37   0.172    -.9598101      .17098
                               IN  |   .1277181   .2342384     0.55   0.586    -.3313807    .5868169
                               IA  |  -.3074279   .2208542    -1.39   0.164    -.7402941    .1254384
                               KS  |  -.5489781   .2269473    -2.42   0.016    -.9937866   -.1041696
                               KY  |  -.8118887   .2374382    -3.42   0.001    -1.277259   -.3465183
                               LA  |  -.3434393   .2497323    -1.38   0.169    -.8329057     .146027
                               ME  |   .1849485   .2444892     0.76   0.449    -.2942415    .6641386
                               MD  |  -.4369056   .2364424    -1.85   0.065    -.9003242     .026513
                               MA  |  -1.065537   .2666702    -4.00   0.000    -1.588201   -.5428731
                               MI  |  -.3496174   .2366052    -1.48   0.140     -.813355    .1141203
                               MN  |  -.9795967   .2251528    -4.35   0.000    -1.420888   -.5383054
                               MS  |  -.5658047   .2489902    -2.27   0.023    -1.053816   -.0777929
                               MO  |  -1.091504   .2314149    -4.72   0.000    -1.545069   -.6379394
                               MT  |   .1691514   .2047438     0.83   0.409     -.232139    .5704417
                               NE  |  -.2307015   .2256076    -1.02   0.307    -.6728842    .2114812
                               NV  |  -.2566648   .2268787    -1.13   0.258    -.7013389    .1880093
                               NH  |   .0673188   .2417316     0.28   0.781    -.4064663     .541104
                               NJ  |   -.835969   .2586301    -3.23   0.001    -1.342875   -.3290633
                               NM  |  -.2578871   .2347796    -1.10   0.272    -.7180467    .2022725
                               NY  |  -.2012437   .3048449    -0.66   0.509    -.7987287    .3962413
                               NC  |  -.9560659   .2161627    -4.42   0.000    -1.379737   -.5323947
                               ND  |   .2226899   .2054266     1.08   0.278    -.1799388    .6253187
                               OH  |  -.9561178   .2358251    -4.05   0.000    -1.418327    -.493909
                               OK  |  -.7989965   .2279037    -3.51   0.000     -1.24568   -.3523134
                               OR  |  -.3182658   .2248575    -1.42   0.157    -.7589785    .1224469
                               PA  |  -1.466266   .2569792    -5.71   0.000    -1.969936   -.9625957
                               RI  |   .3960384    .240397     1.65   0.099     -.075131    .8672078
                               SC  |   -.434628   .2319624    -1.87   0.061     -.889266      .02001
                               SD  |    .076803   .2277228     0.34   0.736    -.3695255    .5231314
                               TN  |  -1.131338   .2350654    -4.81   0.000    -1.592058   -.6706184
                               TX  |  -1.245401   .2258436    -5.51   0.000    -1.688046   -.8027554
                               UT  |  -.3692784     .20978    -1.76   0.078    -.7804396    .0418828
                               VT  |  -.0581917   .2315461    -0.25   0.802    -.5120136    .3956303
                               VA  |  -.7031821   .2705374    -2.60   0.009    -1.233426   -.1729386
                               WA  |  -.9891452   .2215726    -4.46   0.000     -1.42342   -.5548709
                               WV  |  -.4904082   .2651731    -1.85   0.064    -1.010138    .0293216
                               WI  |  -.5345467   .2221096    -2.41   0.016    -.9698736   -.0992198
                               WY  |   .1794183   .2104176     0.85   0.394    -.2329926    .5918291
                                   |
                              year |
                             1984  |   .0662276   .0898342     0.74   0.461    -.1098441    .2422993
                             1988  |   .1299014   .0872908     1.49   0.137    -.0411855    .3009882
                             1994  |    .022564   .0927151     0.24   0.808    -.1591542    .2042823
                             1998  |  -.1963388    .098583    -1.99   0.046    -.3895579   -.0031197
                             2004  |  -.2686975   .1042481    -2.58   0.010    -.4730201   -.0643749
                             2008  |  -.2719732   .1206671    -2.25   0.024    -.5084764     -.03547
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -3.482909   .6593053                     -4.775123   -2.190694
                             /cut2 |  -.4753503   .6513309                     -1.751935    .8012347
                             /cut3 |   .8096514   .6510879                     -.4664573     2.08576
                             /cut4 |   2.816103   .6530131                      1.536221    4.095985
----------------------------------------------------------------------------------------------------

. est sto a6

. 
. ologit reve_1c b2.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_emplo
> y_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.ye
> ar , r 

Iteration 0:   log pseudolikelihood = -10351.868  
Iteration 1:   log pseudolikelihood = -9378.5499  
Iteration 2:   log pseudolikelihood =  -9360.604  
Iteration 3:   log pseudolikelihood = -9360.5601  
Iteration 4:   log pseudolikelihood = -9360.5601  

Ordered logistic regression                     Number of obs     =      7,543
                                                Wald chi2(93)     =    1799.99
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -9360.5601               Pseudo R2         =     0.0958

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1c |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                        White Man  |   .5317392   .0991337     5.36   0.000     .3374408    .7260377
                      White Woman  |   .3785118   .1120691     3.38   0.001     .1588604    .5981632
                   Woman of Color  |  -.1031955    .199773    -0.52   0.605    -.4947434    .2883524
                                   |
                     civil_service |
                              Yes  |  -.4786386    .055548    -8.62   0.000    -.5875107   -.3697665
                      weekly_hours |   .0395543   .0029311    13.49   0.000     .0338095    .0452991
                               age |  -.0155138   .0219281    -0.71   0.479     -.058492    .0274645
                             age_2 |   6.43e-06   .0002187     0.03   0.977    -.0004222    .0004351
                                   |
                               edu |
              High school or less  |   .0429885   .2095777     0.21   0.837    -.3677762    .4537532
                     Some college  |  -.1672944   .1075566    -1.56   0.120    -.3781014    .0435126
                   Graduate study  |   .1129532   .0758331     1.49   0.136    -.0356769    .2615833
                  Graduate degree  |   .0497169    .060836     0.82   0.414    -.0695195    .1689534
                                   |
                years_employ_state |   .0049376    .003876     1.27   0.203    -.0026593    .0125345
               years_employ_agency |  -.0098846   .0041501    -2.38   0.017    -.0180186   -.0017505
             years_employ_position |   .0077178   .0053947     1.43   0.153    -.0028557    .0182912
                                   |
                              pid5 |
                       Republican  |   .2280009   .0778427     2.93   0.003      .075432    .3805697
                  Lean Republican  |  -.0335429   .0991719    -0.34   0.735    -.2279163    .1608306
                  Lean Democratic  |   -.002536   .0930573    -0.03   0.978     -.184925     .179853
                       Democratic  |   .1816716   .0728001     2.50   0.013      .038986    .3243572
                                   |
                       agency_size |
                           25-100  |   .2577081   .0703178     3.66   0.000     .1198877    .3955285
                          101-500  |   .4706283   .0811016     5.80   0.000      .311672    .6295846
                        501-1,000  |   .5575088   .1073675     5.19   0.000     .3470723    .7679452
                      1,001-5,000  |   .6310467   .1140187     5.53   0.000     .4075741    .8545194
                       Over 5,000  |   .8554307   .1566426     5.46   0.000     .5484169    1.162444
                                   |
                 log_agency_budget |   .1545551   .0190955     8.09   0.000     .1171286    .1919815
                      inst6017_nom |   .0036019   .0026201     1.37   0.169    -.0015333    .0087371
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.7217645   .1543915    -4.67   0.000    -1.024366   -.4191628
                Staff: Non-Fiscal  |  -1.344385   .1442132    -9.32   0.000    -1.627038   -1.061732
Income Security & Social Services  |  -1.544121   .1327481   -11.63   0.000    -1.804302   -1.283939
                        Education  |  -1.333907   .1431981    -9.32   0.000     -1.61457   -1.053244
                           Health  |  -1.444351    .138387   -10.44   0.000    -1.715585   -1.173118
                Natural Resources  |  -.9783398   .1251478    -7.82   0.000    -1.223625   -.7330546
             Environment & Energy  |  -1.157852   .1281523    -9.03   0.000    -1.409025   -.9066778
             Economic Development  |  -1.169661   .1311787    -8.92   0.000    -1.426767   -.9125557
                 Criminal Justice  |  -1.490325   .1327232   -11.23   0.000    -1.750458   -1.230192
                       Regulatory  |  -1.341997   .1238209   -10.84   0.000    -1.584681   -1.099312
                   Transportation  |   -.921331   .1483283    -6.21   0.000    -1.212049   -.6306128
                            Other  |  -1.484794   .1321397   -11.24   0.000    -1.743783   -1.225804
                                   |
                             state |
                               AK  |   .1844862   .2185489     0.84   0.399    -.2438617    .6128342
                               AZ  |   .0686257   .2388438     0.29   0.774    -.3994995    .5367509
                               AR  |   .5962324   .2429482     2.45   0.014     .1200627    1.072402
                               CA  |  -.0899827   .2443573    -0.37   0.713    -.5689141    .3889488
                               CO  |   .3909344   .2112609     1.85   0.064    -.0231294    .8049982
                               CT  |   .1792289   .2429228     0.74   0.461    -.2968911    .6553489
                               DE  |   .1713338   .2274411     0.75   0.451    -.2744427    .6171102
                               FL  |  -.5273958   .2248197    -2.35   0.019    -.9680344   -.0867573
                               GA  |   .3733606   .2261473     1.65   0.099      -.06988    .8166013
                               HI  |  -.4723271   .2657496    -1.78   0.076    -.9931867    .0485325
                               ID  |  -.0087548   .2270013    -0.04   0.969    -.4536692    .4361596
                               IL  |   .1443683   .2490528     0.58   0.562    -.3437662    .6325027
                               IN  |  -.2772225   .2239881    -1.24   0.216    -.7162311    .1617862
                               IA  |  -.0552067   .2152792    -0.26   0.798    -.4771462    .3667327
                               KS  |   .5429078   .2175227     2.50   0.013     .1165712    .9692445
                               KY  |   -.493915   .2355542    -2.10   0.036    -.9555926   -.0322373
                               LA  |   .6365047   .2605336     2.44   0.015     .1258682    1.147141
                               ME  |   .8528493   .2276178     3.75   0.000     .4067265    1.298972
                               MD  |   .2340007    .218611     1.07   0.284     -.194469    .6624704
                               MA  |    .473201   .2536004     1.87   0.062    -.0238466    .9702486
                               MI  |   .8221413   .2281193     3.60   0.000     .3750357    1.269247
                               MN  |   .3196358   .2101994     1.52   0.128    -.0923475     .731619
                               MS  |   .3302594    .238284     1.39   0.166    -.1367686    .7972874
                               MO  |   .3331271   .2166495     1.54   0.124    -.0914981    .7577523
                               MT  |  -.2830532   .2152178    -1.32   0.188    -.7048723    .1387659
                               NE  |  -.0741863    .218658    -0.34   0.734    -.5027482    .3543756
                               NV  |  -.7577281   .2102203    -3.60   0.000    -1.169752   -.3457039
                               NH  |   1.064797   .2139455     4.98   0.000     .6454716    1.484122
                               NJ  |  -.4378222   .2409223    -1.82   0.069    -.9100212    .0343767
                               NM  |  -.4457853   .2325061    -1.92   0.055    -.9014888    .0099182
                               NY  |  -.5236403    .270506    -1.94   0.053    -1.053822    .0065417
                               NC  |  -.1303479   .2013047    -0.65   0.517    -.5248978     .264202
                               ND  |  -.3949463   .2050011    -1.93   0.054    -.7967411    .0068485
                               OH  |  -.3798706   .2215315    -1.71   0.086    -.8140643    .0543231
                               OK  |    .767976    .230308     3.33   0.001     .3165807    1.219371
                               OR  |  -.2785938   .2128417    -1.31   0.191    -.6957559    .1385682
                               PA  |   .1065086   .2358795     0.45   0.652    -.3558068     .568824
                               RI  |  -.0517783   .2449748    -0.21   0.833    -.5319201    .4283636
                               SC  |   1.077082   .2380934     4.52   0.000     .6104275    1.543737
                               SD  |  -.8420329   .2224203    -3.79   0.000    -1.277969   -.4060971
                               TN  |   .0646205   .2385057     0.27   0.786    -.4028422    .5320831
                               TX  |  -.0094745   .2401865    -0.04   0.969    -.4802313    .4612823
                               UT  |  -.5591416   .2109727    -2.65   0.008    -.9726406   -.1456426
                               VT  |   .7496343   .2296456     3.26   0.001     .2995372    1.199731
                               VA  |  -.3137102   .2323159    -1.35   0.177    -.7690411    .1416206
                               WA  |  -.4032374   .2156546    -1.87   0.062    -.8259127    .0194378
                               WV  |  -.3648495   .2244198    -1.63   0.104    -.8047042    .0750051
                               WI  |   .2197584   .2066504     1.06   0.288     -.185269    .6247858
                               WY  |  -.7727914   .2178966    -3.55   0.000    -1.199861    -.345722
                                   |
                              year |
                             1978  |  -.5116036   .0906929    -5.64   0.000    -.6893584   -.3338489
                             1984  |   -.507846   .0878024    -5.78   0.000    -.6799355   -.3357565
                             1988  |  -.4688999   .0825201    -5.68   0.000    -.6306362   -.3071635
                             1994  |   -.466606     .08734    -5.34   0.000    -.6377892   -.2954228
                             1998  |  -.7226027   .0893663    -8.09   0.000    -.8977575    -.547448
                             2004  |  -.9583222   .0939958   -10.20   0.000    -1.142551   -.7740937
                             2008  |   -.933202   .1098137    -8.50   0.000    -1.148433   -.7179711
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -3.643124   .6196113                      -4.85754   -2.428708
                             /cut2 |   .0376981   .6089501                     -1.155822    1.231218
                             /cut3 |   1.520051   .6092236                      .3259944    2.714107
                             /cut4 |   3.673424   .6102857                      2.477286    4.869562
----------------------------------------------------------------------------------------------------

. est sto a7

. 
. ologit reve_1d b2.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_emplo
> y_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.ye
> ar , r 

Iteration 0:   log pseudolikelihood = -8728.3519  
Iteration 1:   log pseudolikelihood = -8200.6981  
Iteration 2:   log pseudolikelihood = -8194.7582  
Iteration 3:   log pseudolikelihood = -8194.7467  
Iteration 4:   log pseudolikelihood = -8194.7467  

Ordered logistic regression                     Number of obs     =      6,340
                                                Wald chi2(92)     =     999.27
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -8194.7467               Pseudo R2         =     0.0611

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                        White Man  |   .2571474   .1004093     2.56   0.010     .0603487     .453946
                      White Woman  |   .1655842   .1146206     1.44   0.149    -.0590679    .3902364
                   Woman of Color  |  -.3494887   .2205287    -1.58   0.113     -.781717    .0827395
                                   |
                     civil_service |
                              Yes  |  -.2674122   .0601311    -4.45   0.000    -.3852671   -.1495573
                      weekly_hours |   .0295276   .0031084     9.50   0.000     .0234353    .0356198
                               age |  -.0403184   .0252539    -1.60   0.110    -.0898151    .0091784
                             age_2 |   .0002548   .0002524     1.01   0.313    -.0002398    .0007494
                                   |
                               edu |
              High school or less  |   .0765339   .2636174     0.29   0.772    -.4401468    .5932146
                     Some college  |  -.0604091   .1194484    -0.51   0.613    -.2945238    .1737055
                   Graduate study  |   .1352846    .082029     1.65   0.099    -.0254892    .2960584
                  Graduate degree  |   .0574484   .0656242     0.88   0.381    -.0711726    .1860694
                                   |
                years_employ_state |   .0120718   .0040276     3.00   0.003      .004178    .0199657
               years_employ_agency |  -.0078704   .0043119    -1.83   0.068    -.0163215    .0005807
             years_employ_position |    .004455   .0056835     0.78   0.433    -.0066844    .0155945
                                   |
                              pid5 |
                       Republican  |   .0864186    .082324     1.05   0.294    -.0749334    .2477706
                  Lean Republican  |   .0044505   .1093365     0.04   0.968    -.2098452    .2187461
                  Lean Democratic  |  -.0091306   .1026936    -0.09   0.929    -.2104064    .1921451
                       Democratic  |   .0612516    .076418     0.80   0.423    -.0885249    .2110281
                                   |
                       agency_size |
                           25-100  |   .0577822   .0742731     0.78   0.437    -.0877903    .2033547
                          101-500  |   .0949199   .0847446     1.12   0.263    -.0711766    .2610163
                        501-1,000  |   .1025891   .1174273     0.87   0.382    -.1275642    .3327423
                      1,001-5,000  |  -.0089695   .1225841    -0.07   0.942    -.2492299    .2312908
                       Over 5,000  |   .2036781    .166484     1.22   0.221    -.1226246    .5299808
                                   |
                 log_agency_budget |   .0999747   .0206675     4.84   0.000     .0594671    .1404823
                      inst6017_nom |   .0060982   .0029472     2.07   0.039     .0003217    .0118747
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.1229972   .1637844    -0.75   0.453    -.4440087    .1980144
                Staff: Non-Fiscal  |  -.8768568   .1644321    -5.33   0.000    -1.199138   -.5545758
Income Security & Social Services  |  -.9503731   .1509034    -6.30   0.000    -1.246138    -.654608
                        Education  |  -.6935631   .1615647    -4.29   0.000    -1.010224    -.376902
                           Health  |  -.9182932   .1576484    -5.82   0.000    -1.227278    -.609308
                Natural Resources  |  -.9120763   .1430177    -6.38   0.000    -1.192386   -.6317669
             Environment & Energy  |  -1.032433   .1439321    -7.17   0.000    -1.314535   -.7503316
             Economic Development  |  -1.134385    .147684    -7.68   0.000     -1.42384   -.8449294
                 Criminal Justice  |  -.9563278   .1512715    -6.32   0.000    -1.252815    -.659841
                       Regulatory  |  -1.162944   .1406683    -8.27   0.000    -1.438649   -.8872391
                   Transportation  |  -.8374815   .1672608    -5.01   0.000    -1.165307   -.5096564
                            Other  |  -.9052627   .1495118    -6.05   0.000      -1.1983    -.612225
                                   |
                             state |
                               AK  |   1.399893   .2527265     5.54   0.000     .9045582    1.895228
                               AZ  |   .9238635   .2647702     3.49   0.000     .4049235    1.442804
                               AR  |   .7222201   .2597652     2.78   0.005     .2130896    1.231351
                               CA  |   1.040541   .2968631     3.51   0.000     .4586997    1.622382
                               CO  |   .7062144   .2520423     2.80   0.005     .2122207    1.200208
                               CT  |     .54922   .2832048     1.94   0.052    -.0058512    1.104291
                               DE  |   .0967001   .2752153     0.35   0.725    -.4427119    .6361121
                               FL  |    .917924   .2599173     3.53   0.000     .4084954    1.427353
                               GA  |   .4995448   .2725782     1.83   0.067    -.0346986    1.033788
                               HI  |   -.098179   .2951121    -0.33   0.739    -.6765881    .4802301
                               ID  |   .5452425   .2527906     2.16   0.031      .049782    1.040703
                               IL  |   .5357001   .2844619     1.88   0.060     -.021835    1.093235
                               IN  |   .1926003   .2668031     0.72   0.470    -.3303242    .7155247
                               IA  |   .4623393   .2506624     1.84   0.065      -.02895    .9536285
                               KS  |   1.192527    .257752     4.63   0.000     .6873425    1.697712
                               KY  |   .6270707   .2615218     2.40   0.016     .1144974    1.139644
                               LA  |   .8133197   .2889778     2.81   0.005     .2469336    1.379706
                               ME  |   .8874817   .2850533     3.11   0.002     .3287874    1.446176
                               MD  |   .8027602   .2583373     3.11   0.002     .2964284    1.309092
                               MA  |   .8799829   .2921223     3.01   0.003     .3074338    1.452532
                               MI  |   1.697745   .2692553     6.31   0.000     1.170015    2.225476
                               MN  |   1.185779    .249503     4.75   0.000     .6967623    1.674796
                               MS  |   .4389355   .2610983     1.68   0.093    -.0728077    .9506787
                               MO  |   .7516882   .2590888     2.90   0.004     .2438835    1.259493
                               MT  |   .4021156   .2465757     1.63   0.103    -.0811638    .8853951
                               NE  |   .9359898   .2584906     3.62   0.000     .4293575    1.442622
                               NV  |   .4210234   .2464239     1.71   0.088    -.0619585    .9040053
                               NH  |    .861979   .2763309     3.12   0.002     .3203805    1.403578
                               NJ  |   .3240292   .2653246     1.22   0.222    -.1959976    .8440559
                               NM  |    .450611   .2702053     1.67   0.095    -.0789816    .9802036
                               NY  |   .3916939   .3532072     1.11   0.267    -.3005795    1.083967
                               NC  |   .3156418   .2418451     1.31   0.192    -.1583658    .7896494
                               ND  |  -.6404053   .2569048    -2.49   0.013    -1.143929   -.1368812
                               OH  |   .5187461   .2821676     1.84   0.066    -.0342923    1.071784
                               OK  |   1.100864   .2567021     4.29   0.000      .597737    1.603991
                               OR  |   .6240373   .2571202     2.43   0.015     .1200909    1.127984
                               PA  |   1.029567   .2757739     3.73   0.000     .4890604    1.570074
                               RI  |  -.2562584   .2859077    -0.90   0.370    -.8166271    .3041104
                               SC  |   1.400709   .2775545     5.05   0.000     .8567119    1.944705
                               SD  |  -.2997918   .2582692    -1.16   0.246    -.8059901    .2064065
                               TN  |   .5386902   .2678191     2.01   0.044     .0137745    1.063606
                               TX  |   1.567741   .2655896     5.90   0.000     1.047195    2.088287
                               UT  |   .5426185   .2399215     2.26   0.024     .0723809    1.012856
                               VT  |   .2893295   .2762285     1.05   0.295    -.2520685    .8307275
                               VA  |   .3164445   .2611018     1.21   0.226    -.1953056    .8281945
                               WA  |   .6177409   .2398288     2.58   0.010     .1476851    1.087797
                               WV  |   .1170794   .2607521     0.45   0.653    -.3939852    .6281441
                               WI  |   1.243647   .2552009     4.87   0.000     .7434623    1.743831
                               WY  |  -.2981704   .2535781    -1.18   0.240    -.7951743    .1988335
                                   |
                              year |
                             1984  |  -.0881298   .0899369    -0.98   0.327     -.264403    .0881433
                             1988  |    .154664   .0867667     1.78   0.075    -.0153957    .3247236
                             1994  |   .2173252   .0923942     2.35   0.019     .0362359    .3984145
                             1998  |  -.0626998   .0978743    -0.64   0.522    -.2545298    .1291302
                             2004  |  -.4073416   .1006214    -4.05   0.000    -.6045558   -.2101273
                             2008  |  -.1814891   .1131612    -1.60   0.109    -.4032808    .0403027
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -3.010581   .7002561                     -4.383057   -1.638104
                             /cut2 |   .0478432   .6938314                     -1.312041    1.407728
                             /cut3 |   1.472001   .6940345                       .111718    2.832283
                             /cut4 |   3.636451   .6949337                      2.274406    4.998497
----------------------------------------------------------------------------------------------------

. est sto a8

. 
. 
. est restore a5
(results a5 are active now)

. margins, dydx(3.intersection)

Average marginal effects                        Number of obs     =      7,515
Model VCE    : Robust

dy/dx w.r.t. : 3.intersection
1._predict   : Pr(reve_1a==1), predict(pr outcome(1))
2._predict   : Pr(reve_1a==2), predict(pr outcome(2))
3._predict   : Pr(reve_1a==3), predict(pr outcome(3))
4._predict   : Pr(reve_1a==4), predict(pr outcome(4))
5._predict   : Pr(reve_1a==5), predict(pr outcome(5))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
2.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |   .0503704   .0253158     1.99   0.047     .0007523    .0999885
             2  |   .0152986   .0064067     2.39   0.017     .0027417    .0278554
             3  |  -.0260607   .0128881    -2.02   0.043    -.0513209   -.0008005
             4  |  -.0328359   .0152468    -2.15   0.031     -.062719   -.0029527
             5  |  -.0067724   .0030955    -2.19   0.029    -.0128394   -.0007054
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est restore a6
(results a6 are active now)

. margins, dydx(3.intersection)

Average marginal effects                        Number of obs     =      6,378
Model VCE    : Robust

dy/dx w.r.t. : 3.intersection
1._predict   : Pr(reve_1b==1), predict(pr outcome(1))
2._predict   : Pr(reve_1b==2), predict(pr outcome(2))
3._predict   : Pr(reve_1b==3), predict(pr outcome(3))
4._predict   : Pr(reve_1b==4), predict(pr outcome(4))
5._predict   : Pr(reve_1b==5), predict(pr outcome(5))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
2.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |   .0136056   .0062137     2.19   0.029     .0014269    .0257843
             2  |   .0652933   .0264846     2.47   0.014     .0133845    .1172022
             3  |   .0096587   .0034756     2.78   0.005     .0028466    .0164708
             4  |  -.0407717   .0172143    -2.37   0.018     -.074511   -.0070323
             5  |   -.047786   .0181581    -2.63   0.008    -.0833752   -.0121968
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est restore a7
(results a7 are active now)

. margins, dydx(3.intersection)

Average marginal effects                        Number of obs     =      7,543
Model VCE    : Robust

dy/dx w.r.t. : 3.intersection
1._predict   : Pr(reve_1c==1), predict(pr outcome(1))
2._predict   : Pr(reve_1c==2), predict(pr outcome(2))
3._predict   : Pr(reve_1c==3), predict(pr outcome(3))
4._predict   : Pr(reve_1c==4), predict(pr outcome(4))
5._predict   : Pr(reve_1c==5), predict(pr outcome(5))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
2.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |   .0020048   .0039979     0.50   0.616    -.0058309    .0098405
             2  |   .0180194   .0349835     0.52   0.606    -.0505469    .0865858
             3  |  -.0008745   .0023056    -0.38   0.704    -.0053934    .0036445
             4  |  -.0128984   .0249507    -0.52   0.605    -.0618009    .0360041
             5  |  -.0062513   .0118433    -0.53   0.598    -.0294638    .0169611
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. est restore a8
(results a8 are active now)

. margins, dydx(3.intersection)

Average marginal effects                        Number of obs     =      6,340
Model VCE    : Robust

dy/dx w.r.t. : 3.intersection
1._predict   : Pr(reve_1d==1), predict(pr outcome(1))
2._predict   : Pr(reve_1d==2), predict(pr outcome(2))
3._predict   : Pr(reve_1d==3), predict(pr outcome(3))
4._predict   : Pr(reve_1d==4), predict(pr outcome(4))
5._predict   : Pr(reve_1d==5), predict(pr outcome(5))

---------------------------------------------------------------------------------
                |            Delta-method
                |      dy/dx   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
2.intersection  |  (base outcome)
----------------+----------------------------------------------------------------
3.intersection  |
       _predict |
             1  |   .0115851   .0082059     1.41   0.158    -.0044981    .0276683
             2  |   .0614523   .0388108     1.58   0.113    -.0146153      .13752
             3  |  -.0062088   .0070421    -0.88   0.378    -.0200111    .0075935
             4  |  -.0484556    .030022    -1.61   0.107    -.1072976    .0103864
             5  |   -.018373   .0106469    -1.73   0.084    -.0392405    .0024944
---------------------------------------------------------------------------------
Note: dy/dx for factor levels is the discrete change from the base level.

. 
. **** RESULTS EXPORTED AND FORMATTED IN EXCEL ****
. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B3 ******
. 
. 
. drop if state==27 | state==34 | state==45
(731 observations deleted)

. 
. ologit reve_1a i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r  , r 

Iteration 0:   log pseudolikelihood = -9636.5586  
Iteration 1:   log pseudolikelihood =  -8215.972  
Iteration 2:   log pseudolikelihood =  -8150.845  
Iteration 3:   log pseudolikelihood = -8150.7088  
Iteration 4:   log pseudolikelihood = -8150.7088  

Ordered logistic regression                     Number of obs     =      7,022
                                                Wald chi2(90)     =    2676.53
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -8150.7088               Pseudo R2         =     0.1542

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.2808878   .0732394    -3.84   0.000    -.4244344   -.1373411
                     Man of Color  |  -.1214406   .1027322    -1.18   0.237    -.3227921    .0799108
                   Woman of Color  |  -.5321261   .1702353    -3.13   0.002    -.8657811   -.1984711
                                   |
                     civil_service |
                              Yes  |  -.9580156    .062754   -15.27   0.000    -1.081011   -.8350199
                      weekly_hours |   .0518226   .0032193    16.10   0.000     .0455129    .0581323
                               age |  -.0378022    .023175    -1.63   0.103    -.0832244    .0076199
                             age_2 |   .0005339   .0002281     2.34   0.019     .0000868     .000981
                                   |
                               edu |
              High school or less  |   .1055889   .2082124     0.51   0.612    -.3024998    .5136777
                     Some college  |   .1026787    .110998     0.93   0.355    -.1148734    .3202307
                   Graduate study  |   .0535003   .0803451     0.67   0.505    -.1039731    .2109737
                  Graduate degree  |   -.089182   .0669888    -1.33   0.183    -.2204775    .0421136
                                   |
                years_employ_state |   .0006661   .0043108     0.15   0.877    -.0077829     .009115
               years_employ_agency |  -.0315699     .00457    -6.91   0.000    -.0405269   -.0226129
             years_employ_position |   .0074182   .0057349     1.29   0.196    -.0038221    .0186584
                                   |
                              pid5 |
                       Republican  |   .5006618   .0859031     5.83   0.000     .3322948    .6690289
                  Lean Republican  |   .1323478   .1072636     1.23   0.217     -.077885    .3425805
                  Lean Democratic  |  -.0567998   .1028868    -0.55   0.581    -.2584543    .1448547
                       Democratic  |   .4471856   .0780641     5.73   0.000     .2941828    .6001885
                                   |
                       agency_size |
                           25-100  |   .1169187   .0768756     1.52   0.128    -.0337547    .2675921
                          101-500  |   .4577157   .0879329     5.21   0.000     .2853704    .6300609
                        501-1,000  |   .7079894   .1139834     6.21   0.000     .4845861    .9313927
                      1,001-5,000  |   1.038574   .1182026     8.79   0.000     .8069013    1.270247
                       Over 5,000  |   1.470498   .1568746     9.37   0.000      1.16303    1.777967
                                   |
                 log_agency_budget |    .174041   .0204164     8.52   0.000     .1340256    .2140563
                      inst6017_nom |  -.0023631   .0029505    -0.80   0.423     -.008146    .0034199
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .6085972    .167428     3.63   0.000     .2804445      .93675
                Staff: Non-Fiscal  |  -.3191486   .1638912    -1.95   0.051    -.6403696    .0020723
Income Security & Social Services  |  -1.515969   .1420485   -10.67   0.000    -1.794378   -1.237559
                        Education  |  -.9817351   .1508683    -6.51   0.000    -1.277432   -.6860387
                           Health  |  -1.725474    .152975   -11.28   0.000      -2.0253   -1.425649
                Natural Resources  |  -.8927609   .1316013    -6.78   0.000    -1.150695    -.634827
             Environment & Energy  |  -.8719264   .1406422    -6.20   0.000     -1.14758   -.5962727
             Economic Development  |  -.0580017   .1443223    -0.40   0.688    -.3408682    .2248648
                 Criminal Justice  |  -1.029176   .1413218    -7.28   0.000    -1.306162   -.7521906
                       Regulatory  |  -1.326903   .1353193    -9.81   0.000    -1.592124   -1.061682
                   Transportation  |  -1.109485   .1482552    -7.48   0.000     -1.40006   -.8189103
                            Other  |   -.781022   .1426249    -5.48   0.000    -1.060562   -.5014822
                                   |
                             state |
                               AK  |  -.3260305   .2199691    -1.48   0.138     -.757162     .105101
                               AZ  |  -1.056038   .2461219    -4.29   0.000    -1.538428   -.5736478
                               AR  |   -.220901   .2042742    -1.08   0.280    -.6212711    .1794691
                               CA  |   -2.50441    .244374   -10.25   0.000    -2.983374   -2.025446
                               CO  |  -.0303462   .2134662    -0.14   0.887    -.4487323    .3880398
                               CT  |  -1.150198   .2515019    -4.57   0.000    -1.643132    -.657263
                               DE  |  -.3652821   .2120627    -1.72   0.085    -.7809173    .0503532
                               FL  |  -1.664835   .2443366    -6.81   0.000    -2.143726   -1.185944
                               GA  |  -.9120798   .2309008    -3.95   0.000    -1.364637   -.4595226
                               HI  |  -.7841426   .2452939    -3.20   0.001     -1.26491   -.3033754
                               ID  |   .2554956   .2055117     1.24   0.214    -.1472999    .6582911
                               IL  |  -1.431284    .245211    -5.84   0.000    -1.911888   -.9506787
                               IN  |  -.5646583   .2310639    -2.44   0.015    -1.017535   -.1117813
                               IA  |  -.2734741   .1983239    -1.38   0.168    -.6621817    .1152335
                               KS  |   -.401823   .2283878    -1.76   0.079    -.8494548    .0458088
                               KY  |  -1.049563   .2294115    -4.58   0.000    -1.499202   -.5999252
                               LA  |  -.8118569   .2605447    -3.12   0.002    -1.322515   -.3011987
                               ME  |    -.07441   .2264143    -0.33   0.742    -.5181738    .3693538
                               MD  |  -.9768536    .232929    -4.19   0.000    -1.433386    -.520321
                               MA  |   -1.68823   .2454097    -6.88   0.000    -2.169224   -1.207236
                               MI  |  -.8654288   .2183692    -3.96   0.000    -1.293424    -.437433
                               MN  |  -1.093795   .2254876    -4.85   0.000    -1.535743   -.6518479
                               MS  |  -.2834582     .22507    -1.26   0.208    -.7245872    .1576709
                               MO  |  -1.214935   .2138586    -5.68   0.000     -1.63409   -.7957801
                               MT  |    .146246    .202668     0.72   0.471    -.2509759    .5434679
                               NV  |  -.2293172   .2123885    -1.08   0.280     -.645591    .1869565
                               NH  |  -.0675383   .2238057    -0.30   0.763    -.5061894    .3711128
                               NJ  |  -1.230376   .2332343    -5.28   0.000    -1.687506   -.7732446
                               NM  |   .0489947   .2283171     0.21   0.830    -.3984986    .4964879
                               NY  |  -2.174973   .2692261    -8.08   0.000    -2.702646   -1.647299
                               NC  |  -1.017078   .1960799    -5.19   0.000    -1.401388    -.632769
                               OH  |  -1.222318    .235601    -5.19   0.000    -1.684087   -.7605482
                               OK  |  -.6586101   .2158553    -3.05   0.002    -1.081679   -.2355414
                               OR  |  -.2708638   .2186009    -1.24   0.215    -.6993137     .157586
                               PA  |  -1.870974   .2286407    -8.18   0.000    -2.319102   -1.422847
                               RI  |   .2199361   .2280175     0.96   0.335      -.22697    .6668423
                               SC  |  -.5390675   .2143954    -2.51   0.012    -.9592749   -.1188602
                               SD  |    .336999   .2147668     1.57   0.117    -.0839363    .7579342
                               TN  |  -1.167505    .233093    -5.01   0.000    -1.624359   -.7106508
                               TX  |   -1.96913   .2151467    -9.15   0.000     -2.39081   -1.547451
                               UT  |   .0545164   .2048766     0.27   0.790    -.3470343     .456067
                               VA  |  -1.098719   .2330229    -4.72   0.000    -1.555436   -.6420027
                               WA  |  -.9848948   .2316886    -4.25   0.000    -1.438996   -.5307934
                               WV  |  -.5026075   .2187099    -2.30   0.022    -.9312711   -.0739439
                               WI  |  -.4392487   .2171345    -2.02   0.043    -.8648246   -.0136729
                               WY  |   .5374576   .1961661     2.74   0.006     .1529791    .9219362
                                   |
                              year |
                             1978  |  -.6426145   .0918798    -6.99   0.000    -.8226957   -.4625334
                             1984  |  -.6535023   .0870111    -7.51   0.000    -.8240409   -.4829637
                             1988  |  -.9551243   .0823175   -11.60   0.000    -1.116464    -.793785
                             1994  |  -.8266431   .0886937    -9.32   0.000    -1.000479   -.6528067
                             1998  |  -1.147822   .0953487   -12.04   0.000    -1.334702   -.9609421
                             2004  |  -1.188806    .098004   -12.13   0.000     -1.38089   -.9967215
                             2008  |  -1.560358   .1251249   -12.47   0.000    -1.805598   -1.315117
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.582477   .6435839                     -2.843878   -.3210756
                             /cut2 |   1.058258   .6429962                     -.2019917    2.318507
                             /cut3 |   2.539038   .6444763                      1.275887    3.802188
                             /cut4 |   5.053189     .65363                      3.772097     6.33428
----------------------------------------------------------------------------------------------------

. est sto b1

. ologit reve_1b i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r , r 

Iteration 0:   log pseudolikelihood = -8629.5064  
Iteration 1:   log pseudolikelihood = -7605.0176  
Iteration 2:   log pseudolikelihood = -7579.4165  
Iteration 3:   log pseudolikelihood = -7579.3757  
Iteration 4:   log pseudolikelihood = -7579.3757  

Ordered logistic regression                     Number of obs     =      5,963
                                                Wald chi2(89)     =    1885.28
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -7579.3757               Pseudo R2         =     0.1217

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1b |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.1515376   .0688855    -2.20   0.028    -.2865507   -.0165246
                     Man of Color  |  -.0460409   .1056081    -0.44   0.663    -.2530291    .1609472
                   Woman of Color  |  -.5210482   .1690667    -3.08   0.002    -.8524129   -.1896834
                                   |
                     civil_service |
                              Yes  |  -.7703018    .063205   -12.19   0.000    -.8941814   -.6464223
                      weekly_hours |   .0472956    .003426    13.81   0.000     .0405809    .0540104
                               age |  -.0844751   .0240249    -3.52   0.000     -.131563   -.0373872
                             age_2 |   .0007729   .0002358     3.28   0.001     .0003108     .001235
                                   |
                               edu |
              High school or less  |   .2499407   .2330228     1.07   0.283    -.2067755     .706657
                     Some college  |   .1985687   .1236837     1.61   0.108    -.0438468    .4409842
                   Graduate study  |   .1657574   .0864728     1.92   0.055    -.0037261    .3352409
                  Graduate degree  |   .0827333   .0712436     1.16   0.246    -.0569015    .2223681
                                   |
                years_employ_state |   .0066786   .0044067     1.52   0.130    -.0019584    .0153155
               years_employ_agency |  -.0287181   .0046258    -6.21   0.000    -.0377844   -.0196518
             years_employ_position |  -.0067717   .0063269    -1.07   0.284    -.0191722    .0056288
                                   |
                              pid5 |
                       Republican  |   .3808716   .0886242     4.30   0.000     .2071714    .5545717
                  Lean Republican  |  -.0149457    .113241    -0.13   0.895     -.236894    .2070026
                  Lean Democratic  |  -.0885266   .1020758    -0.87   0.386    -.2885915    .1115383
                       Democratic  |   .3003848   .0827126     3.63   0.000      .138271    .4624985
                                   |
                       agency_size |
                           25-100  |  -.0949064   .0825972    -1.15   0.251    -.2567939    .0669811
                          101-500  |   .1492591   .0933905     1.60   0.110     -.033783    .3323012
                        501-1,000  |   .3077693   .1227529     2.51   0.012      .067178    .5483605
                      1,001-5,000  |   .6057624   .1285788     4.71   0.000     .3537527    .8577721
                       Over 5,000  |   1.010893   .1750651     5.77   0.000     .6677721    1.354015
                                   |
                 log_agency_budget |    .184197   .0221652     8.31   0.000      .140754    .2276401
                      inst6017_nom |   .0032002   .0032606     0.98   0.326    -.0031905    .0095909
                                   |
                          funcat13 |
                    Staff: Fiscal  |   1.299257   .1803499     7.20   0.000     .9457782    1.652737
                Staff: Non-Fiscal  |   .8474722    .188635     4.49   0.000     .4777544     1.21719
Income Security & Social Services  |  -.4926702   .1564414    -3.15   0.002    -.7992897   -.1860506
                        Education  |  -.4389644   .1660736    -2.64   0.008    -.7644626   -.1134661
                           Health  |  -.6880056    .163387    -4.21   0.000    -1.008238   -.3677729
                Natural Resources  |  -.1948578   .1477056    -1.32   0.187    -.4843554    .0946398
             Environment & Energy  |  -.0344501   .1533873    -0.22   0.822    -.3350837    .2661835
             Economic Development  |   .6764053   .1562109     4.33   0.000     .3702376     .982573
                 Criminal Justice  |  -.0696835   .1580719    -0.44   0.659    -.3794987    .2401316
                       Regulatory  |  -.6965288   .1472897    -4.73   0.000    -.9852113   -.4078463
                   Transportation  |  -.3247231   .1667792    -1.95   0.052    -.6516043    .0021582
                            Other  |    .106741   .1569717     0.68   0.497    -.2009179    .4143999
                                   |
                             state |
                               AK  |  -.0762584   .2304606    -0.33   0.741    -.5279528    .3754359
                               AZ  |  -.3639799    .237957    -1.53   0.126     -.830367    .1024073
                               AR  |   .3358909   .2237266     1.50   0.133    -.1026051    .7743869
                               CA  |   -1.53293   .2541146    -6.03   0.000    -2.030985   -1.034874
                               CO  |   -.279322   .2235859    -1.25   0.212    -.7175424    .1588983
                               CT  |  -.8200021   .2647619    -3.10   0.002    -1.338926   -.3010783
                               DE  |  -.8554707   .2237472    -3.82   0.000    -1.294007   -.4169342
                               FL  |  -1.304492   .2383882    -5.47   0.000    -1.771724   -.8372594
                               GA  |  -.8076931    .253968    -3.18   0.001    -1.305461    -.309925
                               HI  |   -1.39136   .2665535    -5.22   0.000    -1.913796   -.8689252
                               ID  |   .7117626   .2222362     3.20   0.001     .2761877    1.147338
                               IL  |  -.3899259   .2870293    -1.36   0.174     -.952493    .1726412
                               IN  |    .118384   .2321592     0.51   0.610    -.3366397    .5734078
                               IA  |  -.3061122    .218762    -1.40   0.162    -.7348779    .1226535
                               KS  |  -.5492253   .2252451    -2.44   0.015    -.9906975    -.107753
                               KY  |  -.8049298   .2361941    -3.41   0.001    -1.267862   -.3419978
                               LA  |   -.350658   .2483484    -1.41   0.158     -.837412     .136096
                               ME  |   .1748588   .2435756     0.72   0.473    -.3025406    .6522581
                               MD  |  -.4335649    .235822    -1.84   0.066    -.8957676    .0286378
                               MA  |  -1.064599   .2648171    -4.02   0.000    -1.583631   -.5455671
                               MI  |   -.347833   .2350302    -1.48   0.139    -.8084837    .1128178
                               MN  |  -.9692621   .2237854    -4.33   0.000    -1.407873   -.5306508
                               MS  |  -.5667007   .2465329    -2.30   0.022    -1.049896   -.0835051
                               MO  |  -1.084291   .2296263    -4.72   0.000     -1.53435   -.6342317
                               MT  |   .1598632    .203758     0.78   0.433    -.2394951    .5592216
                               NV  |  -.2577598   .2249549    -1.15   0.252    -.6986633    .1831436
                               NH  |   .0602538   .2407987     0.25   0.802    -.4117029    .5322105
                               NJ  |  -.8424003   .2574892    -3.27   0.001     -1.34707   -.3377307
                               NM  |  -.2679385   .2331029    -1.15   0.250    -.7248117    .1889347
                               NY  |  -.1988688   .3035449    -0.66   0.512    -.7938059    .3960682
                               NC  |   -.944859   .2148075    -4.40   0.000    -1.365874    -.523844
                               OH  |  -.9390942   .2341265    -4.01   0.000    -1.397974   -.4802148
                               OK  |  -.7932273    .226286    -3.51   0.000     -1.23674    -.349715
                               OR  |  -.3185385   .2238649    -1.42   0.155    -.7573057    .1202287
                               PA  |  -1.455572   .2559635    -5.69   0.000    -1.957251   -.9538928
                               RI  |   .3829508   .2388704     1.60   0.109    -.0852266    .8511282
                               SC  |  -.4322633   .2301219    -1.88   0.060     -.883294    .0187674
                               SD  |   .0576341   .2260052     0.26   0.799     -.385328    .5005962
                               TN  |  -1.121039    .233774    -4.80   0.000    -1.579228   -.6628504
                               TX  |  -1.229173   .2242749    -5.48   0.000    -1.668744    -.789602
                               UT  |  -.3652713   .2083664    -1.75   0.080    -.7736619    .0431194
                               VA  |  -.6943975   .2690233    -2.58   0.010    -1.221673   -.1671216
                               WA  |  -.9798137   .2206157    -4.44   0.000    -1.412212   -.5474149
                               WV  |  -.4949238   .2642095    -1.87   0.061    -1.012765    .0229173
                               WI  |  -.5369223   .2204022    -2.44   0.015    -.9689027    -.104942
                               WY  |   .1644959   .2089645     0.79   0.431    -.2450671    .5740588
                                   |
                              year |
                             1984  |   .0694734   .0933887     0.74   0.457     -.113565    .2525118
                             1988  |   .1319071   .0908644     1.45   0.147    -.0461838    .3099981
                             1994  |   .0090802   .0969863     0.09   0.925    -.1810095    .1991699
                             1998  |  -.2126191   .1029105    -2.07   0.039      -.41432   -.0109182
                             2004  |  -.2641609   .1075706    -2.46   0.014    -.4749954   -.0533263
                             2008  |  -.3251678   .1246177    -2.61   0.009     -.569414   -.0809216
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -3.827451   .6808378                     -5.161868   -2.493033
                             /cut2 |  -.8627528   .6723282                     -2.180492    .4549862
                             /cut3 |   .4244775   .6720293                     -.8926757    1.741631
                             /cut4 |   2.407893   .6737844                      1.087299    3.728486
----------------------------------------------------------------------------------------------------

. est sto b2

. ologit reve_1c i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r , r 

Iteration 0:   log pseudolikelihood = -9690.6947  
Iteration 1:   log pseudolikelihood = -8783.4482  
Iteration 2:   log pseudolikelihood = -8766.6089  
Iteration 3:   log pseudolikelihood = -8766.5674  
Iteration 4:   log pseudolikelihood = -8766.5674  

Ordered logistic regression                     Number of obs     =      7,047
                                                Wald chi2(90)     =    1661.98
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -8766.5674               Pseudo R2         =     0.0954

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1c |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.1406298   .0681341    -2.06   0.039    -.2741701   -.0070894
                     Man of Color  |  -.5027745   .1006324    -5.00   0.000    -.7000104   -.3055385
                   Woman of Color  |  -.6122059   .1812096    -3.38   0.001    -.9673702   -.2570416
                                   |
                     civil_service |
                              Yes  |    -.47589     .05771    -8.25   0.000    -.5889995   -.3627804
                      weekly_hours |   .0395101   .0030182    13.09   0.000     .0335945    .0454257
                               age |  -.0140503      .0228    -0.62   0.538    -.0587376     .030637
                             age_2 |  -.0000147   .0002273    -0.06   0.948    -.0004602    .0004308
                                   |
                               edu |
              High school or less  |   .0981968    .213213     0.46   0.645    -.3196929    .5160866
                     Some college  |  -.1626149   .1115871    -1.46   0.145    -.3813217    .0560919
                   Graduate study  |   .1135388   .0785501     1.45   0.148    -.0404166    .2674943
                  Graduate degree  |    .040501   .0631996     0.64   0.522    -.0833679    .1643698
                                   |
                years_employ_state |   .0057967    .003988     1.45   0.146    -.0020196    .0136131
               years_employ_agency |  -.0096116    .004294    -2.24   0.025    -.0180278   -.0011955
             years_employ_position |   .0085942    .005717     1.50   0.133    -.0026108    .0197993
                                   |
                              pid5 |
                       Republican  |   .2468423   .0812485     3.04   0.002     .0875982    .4060865
                  Lean Republican  |   .0024111    .104195     0.02   0.982    -.2018073    .2066295
                  Lean Democratic  |   -.009257   .0977392    -0.09   0.925    -.2008224    .1823083
                       Democratic  |   .1536849   .0759995     2.02   0.043     .0047286    .3026411
                                   |
                       agency_size |
                           25-100  |     .24197   .0739666     3.27   0.001     .0969982    .3869418
                          101-500  |   .4652067   .0845844     5.50   0.000     .2994243     .630989
                        501-1,000  |   .5425369   .1116074     4.86   0.000     .3237904    .7612834
                      1,001-5,000  |    .626657   .1178341     5.32   0.000     .3957064    .8576075
                       Over 5,000  |   .8545574   .1602645     5.33   0.000     .5404447     1.16867
                                   |
                 log_agency_budget |   .1488577   .0197457     7.54   0.000     .1101568    .1875586
                      inst6017_nom |   .0036366   .0027087     1.34   0.179    -.0016725    .0089456
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.8160936    .159695    -5.11   0.000     -1.12909   -.5030972
                Staff: Non-Fiscal  |  -1.452035   .1499973    -9.68   0.000    -1.746024   -1.158045
Income Security & Social Services  |  -1.604394   .1383253   -11.60   0.000    -1.875506   -1.333281
                        Education  |  -1.388898   .1487763    -9.34   0.000    -1.680494   -1.097302
                           Health  |  -1.510489   .1429815   -10.56   0.000    -1.790728    -1.23025
                Natural Resources  |  -1.077299   .1301091    -8.28   0.000    -1.332308   -.8222896
             Environment & Energy  |  -1.221994   .1330701    -9.18   0.000    -1.482806   -.9611814
             Economic Development  |  -1.260083   .1363363    -9.24   0.000    -1.527297    -.992869
                 Criminal Justice  |   -1.55839   .1380823   -11.29   0.000    -1.829026   -1.287753
                       Regulatory  |  -1.465516   .1289279   -11.37   0.000     -1.71821   -1.212822
                   Transportation  |   -.987647   .1554779    -6.35   0.000    -1.292378   -.6829159
                            Other  |  -1.596431   .1375625   -11.61   0.000    -1.866048   -1.326813
                                   |
                             state |
                               AK  |   .1843497   .2173652     0.85   0.396    -.2416783    .6103778
                               AZ  |   .0655122   .2374387     0.28   0.783    -.3998591    .5308835
                               AR  |    .598209   .2417873     2.47   0.013     .1243146    1.072103
                               CA  |  -.0933322   .2438218    -0.38   0.702    -.5712141    .3845496
                               CO  |   .3934752   .2098647     1.87   0.061    -.0178521    .8048025
                               CT  |   .1706353   .2419901     0.71   0.481    -.3036565    .6449271
                               DE  |   .1608792   .2260787     0.71   0.477     -.282227    .6039854
                               FL  |  -.5083456    .223492    -2.27   0.023    -.9463818   -.0703095
                               GA  |   .3774317   .2249243     1.68   0.093    -.0634119    .8182753
                               HI  |    -.47264   .2646732    -1.79   0.074    -.9913899    .0461099
                               ID  |  -.0166691   .2250623    -0.07   0.941    -.4577831    .4244449
                               IL  |   .1438702   .2479357     0.58   0.562    -.3420748    .6298152
                               IN  |  -.2906091   .2225703    -1.31   0.192    -.7268388    .1456207
                               IA  |  -.0552046   .2140543    -0.26   0.796    -.4747432     .364334
                               KS  |   .5350835   .2164112     2.47   0.013     .1109253    .9592417
                               KY  |  -.4739183   .2342856    -2.02   0.043    -.9331098   -.0147269
                               LA  |   .6425476   .2595102     2.48   0.013     .1339171    1.151178
                               ME  |   .8524434   .2271346     3.75   0.000     .4072678    1.297619
                               MD  |   .2468503   .2177025     1.13   0.257    -.1798387    .6735392
                               MA  |   .4840455   .2525509     1.92   0.055    -.0109452    .9790362
                               MI  |   .8231656   .2264763     3.63   0.000     .3792802    1.267051
                               MN  |   .3248139   .2093081     1.55   0.121    -.0854224    .7350501
                               MS  |   .3198696   .2373467     1.35   0.178    -.1453214    .7850606
                               MO  |   .3336776   .2155278     1.55   0.122    -.0887491    .7561042
                               MT  |  -.2794057   .2139204    -1.31   0.192     -.698682    .1398705
                               NV  |  -.7523464   .2091353    -3.60   0.000    -1.162244   -.3424488
                               NH  |    1.04761   .2133864     4.91   0.000     .6293808     1.46584
                               NJ  |  -.4457217   .2396627    -1.86   0.063     -.915452    .0240087
                               NM  |   -.440273   .2313223    -1.90   0.057    -.8936563    .0131104
                               NY  |  -.5120685   .2697465    -1.90   0.058    -1.040762     .016625
                               NC  |  -.1170257   .2001526    -0.58   0.559    -.5093175    .2752661
                               OH  |   -.378572   .2205975    -1.72   0.086    -.8109353    .0537912
                               OK  |   .7796223   .2290043     3.40   0.001      .330782    1.228463
                               OR  |  -.2766833   .2116173    -1.31   0.191    -.6914455    .1380789
                               PA  |   .1129694   .2349553     0.48   0.631    -.3475347    .5734734
                               RI  |  -.0434961   .2439162    -0.18   0.858    -.5215632    .4345709
                               SC  |   1.080381   .2372903     4.55   0.000     .6153008    1.545462
                               SD  |  -.8517327    .220852    -3.86   0.000    -1.284595   -.4188707
                               TN  |   .0709144   .2373937     0.30   0.765    -.3943688    .5361976
                               TX  |  -.0040732   .2390548    -0.02   0.986     -.472612    .4644655
                               UT  |  -.5694669   .2101884    -2.71   0.007    -.9814286   -.1575052
                               VA  |   -.310346   .2313223    -1.34   0.180    -.7637294    .1430374
                               WA  |  -.3994274   .2143682    -1.86   0.062    -.8195814    .0207266
                               WV  |  -.3584999   .2232263    -1.61   0.108    -.7960154    .0790155
                               WI  |   .2159891   .2052213     1.05   0.293    -.1862373    .6182154
                               WY  |  -.7862588    .216487    -3.63   0.000    -1.210566   -.3619522
                                   |
                              year |
                             1978  |  -.4936177   .0940879    -5.25   0.000    -.6780267   -.3092088
                             1984  |  -.4682304   .0908545    -5.15   0.000     -.646302   -.2901587
                             1988  |  -.4494691   .0855286    -5.26   0.000    -.6171022   -.2818361
                             1994  |  -.4515767   .0909072    -4.97   0.000    -.6297515   -.2734018
                             1998  |  -.7144865   .0927672    -7.70   0.000    -.8963068   -.5326661
                             2004  |  -.9622364   .0964745    -9.97   0.000    -1.151323   -.7731498
                             2008  |  -.9724174   .1136145    -8.56   0.000    -1.195098   -.7497371
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -4.173615   .6361078                     -5.420363   -2.926867
                             /cut2 |   -.556684   .6245267                     -1.780734    .6673658
                             /cut3 |   .9200165   .6246477                     -.3042705    2.144303
                             /cut4 |   3.073664   .6255865                      1.847537    4.299791
----------------------------------------------------------------------------------------------------

. est sto b3

. ologit reve_1d i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r , r 

Iteration 0:   log pseudolikelihood = -8146.8704  
Iteration 1:   log pseudolikelihood = -7665.9993  
Iteration 2:   log pseudolikelihood = -7660.6586  
Iteration 3:   log pseudolikelihood = -7660.6486  
Iteration 4:   log pseudolikelihood = -7660.6486  

Ordered logistic regression                     Number of obs     =      5,928
                                                Wald chi2(89)     =     905.46
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -7660.6486               Pseudo R2         =     0.0597

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.0836691   .0705033    -1.19   0.235    -.2218531    .0545148
                     Man of Color  |  -.2426887   .1029783    -2.36   0.018    -.4445224   -.0408551
                   Woman of Color  |   -.599767   .2069408    -2.90   0.004    -1.005364   -.1941705
                                   |
                     civil_service |
                              Yes  |  -.2799131   .0623104    -4.49   0.000    -.4020393   -.1577868
                      weekly_hours |   .0296269   .0032141     9.22   0.000     .0233273    .0359265
                               age |  -.0443086   .0260957    -1.70   0.090    -.0954552    .0068381
                             age_2 |   .0002899    .000261     1.11   0.267    -.0002216    .0008014
                                   |
                               edu |
              High school or less  |   .0793797   .2646452     0.30   0.764    -.4393155    .5980748
                     Some college  |   -.024577   .1221299    -0.20   0.841    -.2639472    .2147932
                   Graduate study  |   .1416687   .0851194     1.66   0.096    -.0251621    .3084996
                  Graduate degree  |   .0310598   .0676923     0.46   0.646    -.1016147    .1637343
                                   |
                years_employ_state |   .0134019   .0041696     3.21   0.001     .0052296    .0215741
               years_employ_agency |  -.0092649   .0044948    -2.06   0.039    -.0180746   -.0004553
             years_employ_position |   .0069722   .0060266     1.16   0.247    -.0048398    .0187842
                                   |
                              pid5 |
                       Republican  |   .0758049   .0858952     0.88   0.377    -.0925466    .2441564
                  Lean Republican  |  -.0031066   .1140075    -0.03   0.978    -.2265572    .2203441
                  Lean Democratic  |  -.0159298   .1077067    -0.15   0.882    -.2270311    .1951715
                       Democratic  |   .0284531    .079238     0.36   0.720    -.1268505    .1837567
                                   |
                       agency_size |
                           25-100  |   .0626718   .0776471     0.81   0.420    -.0895136    .2148573
                          101-500  |   .1078695   .0879678     1.23   0.220    -.0645442    .2802832
                        501-1,000  |   .1027541   .1212952     0.85   0.397    -.1349802    .3404883
                      1,001-5,000  |  -.0087748   .1261385    -0.07   0.945    -.2560017    .2384521
                       Over 5,000  |   .1962068   .1693128     1.16   0.247    -.1356402    .5280539
                                   |
                 log_agency_budget |   .0947783    .021264     4.46   0.000     .0531016    .1364549
                      inst6017_nom |   .0066385   .0030642     2.17   0.030     .0006327    .0126443
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.1985314   .1726301    -1.15   0.250    -.5368802    .1398175
                Staff: Non-Fiscal  |  -.9768177   .1721225    -5.68   0.000    -1.314172   -.6394637
Income Security & Social Services  |  -.9339978   .1582518    -5.90   0.000    -1.244166     -.62383
                        Education  |  -.7247473   .1699822    -4.26   0.000    -1.057906   -.3915883
                           Health  |  -.9323397   .1647621    -5.66   0.000    -1.255268   -.6094119
                Natural Resources  |  -.9620253   .1502545    -6.40   0.000    -1.256519   -.6675319
             Environment & Energy  |  -1.045519    .150512    -6.95   0.000    -1.340517   -.7505209
             Economic Development  |  -1.183286   .1546452    -7.65   0.000    -1.486385   -.8801868
                 Criminal Justice  |  -.9810895   .1597141    -6.14   0.000    -1.294123   -.6680557
                       Regulatory  |  -1.251794   .1477969    -8.47   0.000    -1.541471   -.9621177
                   Transportation  |  -.8308566   .1760651    -4.72   0.000    -1.175938   -.4857753
                            Other  |  -.9779932   .1573636    -6.21   0.000     -1.28642   -.6695662
                                   |
                             state |
                               AK  |   1.397696    .253956     5.50   0.000      .899951     1.89544
                               AZ  |   .9267541   .2658368     3.49   0.000     .4057236    1.447785
                               AR  |   .7148288   .2611049     2.74   0.006     .2030727    1.226585
                               CA  |   1.049961   .2981872     3.52   0.000     .4655245    1.634397
                               CO  |   .7225573   .2536131     2.85   0.004     .2254849     1.21963
                               CT  |    .540528     .28492     1.90   0.058    -.0179049    1.098961
                               DE  |   .0841241   .2765934     0.30   0.761     -.457989    .6262372
                               FL  |   .9345632   .2613091     3.58   0.000     .4224069     1.44672
                               GA  |    .502293   .2746238     1.83   0.067    -.0359598    1.040546
                               HI  |  -.1078879   .2967675    -0.36   0.716    -.6895416    .4737658
                               ID  |   .5439233    .254809     2.13   0.033     .0445069     1.04334
                               IL  |   .5338509   .2864517     1.86   0.062    -.0275841    1.095286
                               IN  |    .186357    .268151     0.69   0.487    -.3392094    .7119234
                               IA  |   .4622692   .2518509     1.84   0.066    -.0313494    .9558878
                               KS  |    1.19731   .2589907     4.62   0.000     .6896973    1.704922
                               KY  |   .6273115   .2627101     2.39   0.017     .1124093    1.142214
                               LA  |   .8193759   .2908244     2.82   0.005     .2493705    1.389381
                               ME  |   .8861308   .2869338     3.09   0.002     .3237508    1.448511
                               MD  |   .8078311   .2603278     3.10   0.002     .2975979    1.318064
                               MA  |   .8808081   .2929164     3.01   0.003     .3067025    1.454914
                               MI  |   1.714205   .2704239     6.34   0.000     1.184184    2.244226
                               MN  |   1.187817    .250914     4.73   0.000     .6960344    1.679599
                               MS  |   .4358281   .2625582     1.66   0.097    -.0787765    .9504327
                               MO  |   .7537536   .2601372     2.90   0.004      .243894    1.263613
                               MT  |   .4028492   .2480999     1.62   0.104    -.0834177    .8891161
                               NV  |   .4192703   .2480592     1.69   0.091    -.0669167    .9054574
                               NH  |   .8641226   .2776782     3.11   0.002     .3198834    1.408362
                               NJ  |   .3133139   .2669447     1.17   0.241     -.209888    .8365158
                               NM  |   .4519145   .2720316     1.66   0.097    -.0812577    .9850867
                               NY  |    .401975   .3548429     1.13   0.257    -.2935044    1.097454
                               NC  |   .3181095   .2432277     1.31   0.191    -.1586081     .794827
                               OH  |    .521354   .2835177     1.84   0.066    -.0343306    1.077039
                               OK  |   1.109884   .2577982     4.31   0.000     .6046089    1.615159
                               OR  |   .6280899   .2583998     2.43   0.015     .1216357    1.134544
                               PA  |   1.036561   .2766966     3.75   0.000     .4942455    1.578876
                               RI  |  -.2647207   .2879639    -0.92   0.358    -.8291196    .2996783
                               SC  |   1.402261   .2791455     5.02   0.000     .8551455    1.949376
                               SD  |  -.3109668   .2599828    -1.20   0.232    -.8205236    .1985901
                               TN  |   .5378956   .2691452     2.00   0.046     .0103806    1.065411
                               TX  |    1.57843   .2671766     5.91   0.000     1.054774    2.102087
                               UT  |   .5471155   .2417887     2.26   0.024     .0732185    1.021013
                               VA  |    .314624    .262945     1.20   0.231    -.2007388    .8299869
                               WA  |   .6186541   .2416055     2.56   0.010     .1451161    1.092192
                               WV  |   .1144101   .2619626     0.44   0.662    -.3990271    .6278473
                               WI  |   1.243449   .2559513     4.86   0.000      .741794    1.745105
                               WY  |  -.3041837   .2554122    -1.19   0.234    -.8047824     .196415
                                   |
                              year |
                             1984  |  -.0571126   .0929674    -0.61   0.539    -.2393254    .1251001
                             1988  |   .1777273   .0906311     1.96   0.050     .0000936     .355361
                             1994  |    .229193   .0962723     2.38   0.017     .0405028    .4178832
                             1998  |  -.0461833   .1020693    -0.45   0.651    -.2462355    .1538689
                             2004  |    -.38547   .1039938    -3.71   0.000    -.5892941    -.181646
                             2008  |  -.1908271   .1168627    -1.63   0.102    -.4198737    .0382196
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -3.418414   .7132678                     -4.816393   -2.020435
                             /cut2 |  -.3387843   .7070868                     -1.724649     1.04708
                             /cut3 |   1.090101   .7071615                     -.2959099    2.476112
                             /cut4 |   3.257162   .7079069                       1.86969    4.644634
----------------------------------------------------------------------------------------------------

. est sto b4

. ologit d_15a i.intersection i.reve_1a i.reve_1b i.civil_service weekly_hours age age_2 b3.edu years_employ_
> state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fun
> cat13 i.state i.year , r 

Iteration 0:   log pseudolikelihood = -6019.0214  
Iteration 1:   log pseudolikelihood =  -5439.773  
Iteration 2:   log pseudolikelihood = -5410.6997  
Iteration 3:   log pseudolikelihood = -5410.4689  
Iteration 4:   log pseudolikelihood = -5410.4689  

Ordered logistic regression                     Number of obs     =      5,821
                                                Wald chi2(97)     =    1063.50
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -5410.4689               Pseudo R2         =     0.1011

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_15a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.1017473   .0801366    -1.27   0.204    -.2588121    .0553174
                     Man of Color  |   .3117054   .1201373     2.59   0.009     .0762407    .5471702
                   Woman of Color  |   .5610192   .2353561     2.38   0.017     .0997298    1.022309
                                   |
                           reve_1a |
                Less than Monthly  |   .2421671   .0833709     2.90   0.004     .0787631     .405571
                          Monthly  |   .2554334   .1073264     2.38   0.017     .0450776    .4657892
                           Weekly  |   .5631783    .143831     3.92   0.000     .2812746    .8450819
                            Daily  |    1.29845   .3737626     3.47   0.001     .5658884    2.031011
                                   |
                           reve_1b |
                Less than Monthly  |   .3904714   .1881329     2.08   0.038     .0217377    .7592052
                          Monthly  |   .5906652   .1938151     3.05   0.002     .2107946    .9705359
                           Weekly  |   1.092978   .2002405     5.46   0.000     .7005137    1.485442
                            Daily  |   1.646553   .2217335     7.43   0.000     1.211963    2.081143
                                   |
                     civil_service |
                              Yes  |   .1291795   .0714526     1.81   0.071    -.0108651    .2692241
                      weekly_hours |  -.0057757   .0037028    -1.56   0.119    -.0130331    .0014818
                               age |  -.0033813   .0264627    -0.13   0.898    -.0552472    .0484846
                             age_2 |  -.0000561   .0002614    -0.21   0.830    -.0005684    .0004562
                                   |
                               edu |
              High school or less  |   .0330579   .2732578     0.12   0.904    -.5025175    .5686333
                     Some college  |  -.2146285    .140013    -1.53   0.125    -.4890488    .0597919
                   Graduate study  |   .1678151   .0999876     1.68   0.093    -.0281569    .3637871
                  Graduate degree  |  -.0932639   .0785979    -1.19   0.235    -.2473129     .060785
                                   |
                years_employ_state |  -.0005119   .0049416    -0.10   0.917    -.0101974    .0091735
               years_employ_agency |  -.0018056   .0051958    -0.35   0.728    -.0119893     .008378
             years_employ_position |  -.0232986   .0065099    -3.58   0.000    -.0360579   -.0105393
                                   |
                              pid5 |
                       Republican  |  -.0260417   .0974972    -0.27   0.789    -.2171327    .1650494
                  Lean Republican  |  -.0479691   .1242663    -0.39   0.699    -.2915265    .1955883
                  Lean Democratic  |  -.0589576   .1155047    -0.51   0.610    -.2853427    .1674274
                       Democratic  |  -.0786939    .089037    -0.88   0.377    -.2532032    .0958155
                                   |
                       agency_size |
                           25-100  |   .0497855   .0906161     0.55   0.583    -.1278187    .2273898
                          101-500  |  -.1442514   .1007959    -1.43   0.152    -.3418077    .0533049
                        501-1,000  |  -.1264721   .1310594    -0.96   0.335    -.3833438    .1303997
                      1,001-5,000  |  -.2410249   .1391787    -1.73   0.083    -.5138101    .0317603
                       Over 5,000  |  -.1817979   .1901353    -0.96   0.339    -.5544563    .1908604
                                   |
                 log_agency_budget |   .0495304   .0233937     2.12   0.034     .0036795    .0953813
                      inst6017_nom |  -.0015707   .0034669    -0.45   0.651    -.0083657    .0052244
                                   |
                          funcat13 |
                    Staff: Fiscal  |   2.617039   .1943838    13.46   0.000     2.236053    2.998024
                Staff: Non-Fiscal  |   2.897729    .192463    15.06   0.000     2.520509     3.27495
Income Security & Social Services  |   1.928421    .160484    12.02   0.000     1.613878    2.242964
                        Education  |   1.854291   .1728892    10.73   0.000     1.515434    2.193147
                           Health  |   1.908335   .1682481    11.34   0.000     1.578575    2.238095
                Natural Resources  |   1.885961   .1499404    12.58   0.000     1.592083    2.179839
             Environment & Energy  |   2.448019   .1618524    15.13   0.000     2.130794    2.765244
             Economic Development  |   2.192736   .1699339    12.90   0.000     1.859672      2.5258
                 Criminal Justice  |   2.181432   .1631428    13.37   0.000     1.861677    2.501186
                       Regulatory  |   1.804377   .1524176    11.84   0.000     1.505644     2.10311
                   Transportation  |   2.348753   .1864408    12.60   0.000     1.983336     2.71417
                            Other  |   1.829995   .1643907    11.13   0.000     1.507795    2.152194
                                   |
                             state |
                               AK  |   1.103876   .2501174     4.41   0.000     .6136545    1.594097
                               AZ  |   .4936716   .2729885     1.81   0.071    -.0413761    1.028719
                               AR  |   .9104005   .2821034     3.23   0.001      .357488    1.463313
                               CA  |    1.42903   .3057184     4.67   0.000      .829833    2.028227
                               CO  |   .2387543    .247799     0.96   0.335    -.2469227    .7244314
                               CT  |    1.16151   .3231622     3.59   0.000     .5281242    1.794897
                               DE  |   1.262337   .2509036     5.03   0.000     .7705749    1.754099
                               FL  |   .7513947   .2760634     2.72   0.006     .2103204    1.292469
                               GA  |   .9650467   .2598265     3.71   0.000     .4557961    1.474297
                               HI  |   1.157668   .2830282     4.09   0.000     .6029429    1.712393
                               ID  |   .5328995   .2514614     2.12   0.034     .0400442    1.025755
                               IL  |   1.120108   .3116398     3.59   0.000     .5093051     1.73091
                               IN  |   1.015481   .2696758     3.77   0.000     .4869262    1.544036
                               IA  |   .7278574   .2529888     2.88   0.004     .2320084    1.223706
                               KS  |   1.125161   .2740165     4.11   0.000     .5880984    1.662223
                               KY  |   1.116429   .2697472     4.14   0.000     .5877342    1.645124
                               LA  |   .7442227   .3000758     2.48   0.013      .156085     1.33236
                               ME  |   1.060116   .2797536     3.79   0.000     .5118091    1.608423
                               MD  |   1.267986   .2635072     4.81   0.000     .7515212     1.78445
                               MA  |   .6977445   .2719387     2.57   0.010     .1647545    1.230735
                               MI  |   1.239179   .2541541     4.88   0.000     .7410458    1.737312
                               MN  |   .8846224   .2355882     3.75   0.000     .4228779    1.346367
                               MS  |  -.3725522   .2513144    -1.48   0.138    -.8651194    .1200149
                               MO  |   .8259103   .2553719     3.23   0.001     .3253906     1.32643
                               MT  |   .6086477   .2441083     2.49   0.013     .1302043    1.087091
                               NV  |   1.003935   .2622287     3.83   0.000     .4899758    1.517893
                               NH  |   .9658312   .2750136     3.51   0.000     .4268145    1.504848
                               NJ  |   1.618613    .285167     5.68   0.000     1.059696     2.17753
                               NM  |   1.087282   .2761631     3.94   0.000     .5460126    1.628552
                               NY  |   1.676062   .3990862     4.20   0.000     .8938674    2.458257
                               NC  |   .7320891   .2329118     3.14   0.002     .2755903    1.188588
                               OH  |   .8972465   .2656236     3.38   0.001     .3766338    1.417859
                               OK  |   .2538937   .2427978     1.05   0.296    -.2219812    .7297685
                               OR  |   .6003853    .245343     2.45   0.014     .1195219    1.081249
                               PA  |   1.186425   .2586851     4.59   0.000     .6794118    1.693439
                               RI  |   .9762393   .2913452     3.35   0.001     .4052131    1.547266
                               SC  |  -.0844699   .2559756    -0.33   0.741    -.5861728     .417233
                               SD  |   1.055169    .267516     3.94   0.000      .530847    1.579491
                               TN  |   .9628689   .2578862     3.73   0.000     .4574213    1.468316
                               TX  |  -.3726765   .2537373    -1.47   0.142    -.8699925    .1246395
                               UT  |   .9646674   .2356469     4.09   0.000     .5028078    1.426527
                               VA  |   1.157145   .2802492     4.13   0.000     .6078666    1.706423
                               WA  |   .8642691   .2672468     3.23   0.001     .3404751    1.388063
                               WV  |   .5380829   .2671765     2.01   0.044     .0144267    1.061739
                               WI  |   1.577447   .2616161     6.03   0.000     1.064688    2.090205
                               WY  |   .5346856   .2463495     2.17   0.030     .0518495    1.017522
                                   |
                              year |
                             1984  |    .124784    .106186     1.18   0.240    -.0833368    .3329048
                             1988  |    .044768   .1019066     0.44   0.660    -.1549653    .2445013
                             1994  |   .3945245   .1098754     3.59   0.000     .1791727    .6098763
                             1998  |   .6356791   .1176593     5.40   0.000     .4050711    .8662871
                             2004  |   .2565366   .1187135     2.16   0.031     .0238624    .4892109
                             2008  |   .5401127   .1285485     4.20   0.000     .2881623    .7920631
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -.4606217   .7366601                     -1.904449    .9832056
                             /cut2 |   1.494252   .7387478                      .0463326    2.942171
                             /cut3 |   3.081918   .7402159                      1.631121    4.532715
----------------------------------------------------------------------------------------------------

. est sto b5

. ologit d_16a i.intersection i.reve_1c  i.reve_1d i.civil_service weekly_hours age age_2 b3.edu years_employ
> _state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fu
> ncat13 i.state i.year , r 

Iteration 0:   log pseudolikelihood = -6227.2046  
Iteration 1:   log pseudolikelihood = -6009.7792  
Iteration 2:   log pseudolikelihood = -6008.4887  
Iteration 3:   log pseudolikelihood = -6008.4882  

Ordered logistic regression                     Number of obs     =      5,802
                                                Wald chi2(97)     =     415.86
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -6008.4882               Pseudo R2         =     0.0351

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_16a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |   .0556724   .0747111     0.75   0.456    -.0907586    .2021035
                     Man of Color  |   .2785891   .1126467     2.47   0.013     .0578057    .4993725
                   Woman of Color  |   .4323763   .2131829     2.03   0.043     .0145455    .8502071
                                   |
                           reve_1c |
                Less than Monthly  |  -.5248341   .2771941    -1.89   0.058    -1.068125    .0184564
                          Monthly  |  -.4553052   .2796687    -1.63   0.104    -1.003446    .0928353
                           Weekly  |  -.3288004   .2838554    -1.16   0.247    -.8851467    .2275459
                            Daily  |  -.3875065   .3050904    -1.27   0.204    -.9854726    .2104597
                                   |
                           reve_1d |
                Less than Monthly  |   .6945114   .2262189     3.07   0.002     .2511304    1.137892
                          Monthly  |   .8366987   .2266376     3.69   0.000     .3924971      1.2809
                           Weekly  |   1.037594   .2290253     4.53   0.000     .5887123    1.486475
                            Daily  |   1.396999   .2549156     5.48   0.000     .8973741    1.896625
                                   |
                     civil_service |
                              Yes  |   .0732354   .0667892     1.10   0.273     -.057669    .2041398
                      weekly_hours |  -.0006894   .0033158    -0.21   0.835    -.0071882    .0058094
                               age |   .0290224   .0243778     1.19   0.234    -.0187572    .0768021
                             age_2 |  -.0002407    .000242    -0.99   0.320     -.000715    .0002336
                                   |
                               edu |
              High school or less  |   .0182992   .2786446     0.07   0.948    -.5278341    .5644324
                     Some college  |   -.154661   .1288391    -1.20   0.230    -.4071811     .097859
                   Graduate study  |   .0587002   .0905645     0.65   0.517     -.118803    .2362033
                  Graduate degree  |   -.087888   .0732782    -1.20   0.230    -.2315107    .0557347
                                   |
                years_employ_state |   .0071012   .0045878     1.55   0.122    -.0018908    .0160932
               years_employ_agency |  -.0094289   .0048082    -1.96   0.050    -.0188528   -5.00e-06
             years_employ_position |  -.0142586     .00643    -2.22   0.027    -.0268612   -.0016559
                                   |
                              pid5 |
                       Republican  |  -.1865309   .0902794    -2.07   0.039    -.3634753   -.0095864
                  Lean Republican  |   .0175986   .1178559     0.15   0.881    -.2133947    .2485919
                  Lean Democratic  |   .0254208   .1114878     0.23   0.820    -.1930913    .2439329
                       Democratic  |  -.0743053   .0850567    -0.87   0.382    -.2410135    .0924028
                                   |
                       agency_size |
                           25-100  |   .1034003    .084839     1.22   0.223    -.0628811    .2696817
                          101-500  |   .1143128   .0968873     1.18   0.238    -.0755829    .3042086
                        501-1,000  |  -.1200128   .1237143    -0.97   0.332    -.3624883    .1224628
                      1,001-5,000  |  -.1578741   .1317131    -1.20   0.231     -.416027    .1002789
                       Over 5,000  |  -.1615282   .1766047    -0.91   0.360     -.507667    .1846106
                                   |
                 log_agency_budget |   .0357632   .0218346     1.64   0.101    -.0070317    .0785582
                      inst6017_nom |   .0084238   .0033111     2.54   0.011     .0019341    .0149135
                                   |
                          funcat13 |
                    Staff: Fiscal  |   -.081755   .1786325    -0.46   0.647    -.4318682    .2683582
                Staff: Non-Fiscal  |  -.0036196   .1828522    -0.02   0.984    -.3620033    .3547642
Income Security & Social Services  |  -.2287771   .1696833    -1.35   0.178    -.5613503    .1037961
                        Education  |   .0967294   .1906685     0.51   0.612    -.2769741    .4704329
                           Health  |  -.0520251   .1802443    -0.29   0.773    -.4052974    .3012472
                Natural Resources  |  -.2600275   .1607112    -1.62   0.106    -.5750157    .0549606
             Environment & Energy  |   .0687881    .168346     0.41   0.683    -.2611641    .3987402
             Economic Development  |  -.3823337   .1698242    -2.25   0.024    -.7151829   -.0494845
                 Criminal Justice  |   .1917546    .173473     1.11   0.269    -.1482462    .5317555
                       Regulatory  |  -.0065784   .1621339    -0.04   0.968     -.324355    .3111982
                   Transportation  |   .0635891    .180683     0.35   0.725     -.290543    .4177213
                            Other  |  -.5367002   .1698678    -3.16   0.002     -.869635   -.2037655
                                   |
                             state |
                               AK  |    .742241   .2423059     3.06   0.002     .2673302    1.217152
                               AZ  |   .8114748   .2597919     3.12   0.002     .3022921    1.320658
                               AR  |    .605473   .2480628     2.44   0.015     .1192789    1.091667
                               CA  |   .8194695   .2703426     3.03   0.002     .2896078    1.349331
                               CO  |    1.00853   .2534665     3.98   0.000     .5117452    1.505316
                               CT  |   .8260418    .290469     2.84   0.004     .2567331     1.39535
                               DE  |   .9064932   .2478383     3.66   0.000      .420739    1.392247
                               FL  |   1.153948   .2605758     4.43   0.000     .6432292    1.664667
                               GA  |   .4956063   .2682084     1.85   0.065    -.0300725    1.021285
                               HI  |   .5010846    .268304     1.87   0.062    -.0247816    1.026951
                               ID  |   .7483387   .2491411     3.00   0.003     .2600311    1.236646
                               IL  |   .3999022    .269702     1.48   0.138    -.1287039    .9285083
                               IN  |    .582465   .2425838     2.40   0.016     .1070095    1.057921
                               IA  |   .9242478   .2403823     3.84   0.000     .4531071    1.395388
                               KS  |   1.241327   .2571089     4.83   0.000     .7374023    1.745251
                               KY  |   .4943546   .2454344     2.01   0.044      .013312    .9753972
                               LA  |   .1285677   .2644763     0.49   0.627    -.3897962    .6469316
                               ME  |   1.139949   .2729842     4.18   0.000       .60491    1.674988
                               MD  |   .4614333   .2531798     1.82   0.068      -.03479    .9576565
                               MA  |  -.0555323   .2565187    -0.22   0.829    -.5582997    .4472352
                               MI  |   .1554664   .2460735     0.63   0.528    -.3268287    .6377615
                               MN  |   1.177187   .2417219     4.87   0.000     .7034207    1.650953
                               MS  |    .941676   .2549783     3.69   0.000     .4419277    1.441424
                               MO  |   .4210485   .2456549     1.71   0.087    -.0604263    .9025234
                               MT  |   .7237711    .231157     3.13   0.002     .2707118     1.17683
                               NV  |   .9852434   .2457874     4.01   0.000     .5035089    1.466978
                               NH  |   1.325265    .260062     5.10   0.000     .8155526    1.834977
                               NJ  |    .755229   .2595797     2.91   0.004     .2464621    1.263996
                               NM  |   .6974082   .2617488     2.66   0.008       .18439    1.210426
                               NY  |   .5736812   .2822593     2.03   0.042     .0204631    1.126899
                               NC  |   .8039939   .2350366     3.42   0.001     .3433306    1.264657
                               OH  |    .416676   .2501346     1.67   0.096    -.0735788    .9069308
                               OK  |   1.242854   .2559486     4.86   0.000     .7412036    1.744504
                               OR  |   1.341146   .2503377     5.36   0.000     .8504927    1.831798
                               PA  |    .073013   .2442858     0.30   0.765    -.4057784    .5518044
                               RI  |   .4214437   .2702171     1.56   0.119    -.1081721    .9510595
                               SC  |    .790531    .272306     2.90   0.004      .256821    1.324241
                               SD  |    .474038   .2415342     1.96   0.050     .0006397    .9474363
                               TN  |    .204001   .2517278     0.81   0.418    -.2893765    .6973784
                               TX  |   1.266492   .2740091     4.62   0.000     .7294444     1.80354
                               UT  |   1.159014   .2462634     4.71   0.000     .6763469    1.641682
                               VA  |   .9757622   .2667163     3.66   0.000     .4530078    1.498517
                               WA  |   .8108576   .2607651     3.11   0.002     .2997673    1.321948
                               WV  |   .5838602   .2593927     2.25   0.024     .0754599    1.092261
                               WI  |   .7294476   .2435403     3.00   0.003     .2521174    1.206778
                               WY  |   .7709822   .2486755     3.10   0.002     .2835871    1.258377
                                   |
                              year |
                             1984  |   -.000836   .0973105    -0.01   0.993     -.191561     .189889
                             1988  |  -.0564871   .0923759    -0.61   0.541    -.2375405    .1245663
                             1994  |   .1083133   .1000527     1.08   0.279    -.0877864    .3044131
                             1998  |   .3279185    .106559     3.08   0.002     .1190667    .5367703
                             2004  |   .0447989   .1100163     0.41   0.684    -.1708291     .260427
                             2008  |   .1763301   .1189685     1.48   0.138    -.0568439    .4095041
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.634327   .7434465                     -3.091456   -.1771987
                             /cut2 |   .6395824   .7395195                     -.8098492    2.089014
                             /cut3 |   2.501767   .7406554                      1.050109    3.953425
----------------------------------------------------------------------------------------------------

. est sto b6

. ologit d_20a i.intersection i.reve_1a i.reve_1b  i.civil_service weekly_hours age age_2 b3.edu years_employ
> _state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fu
> ncat13 i.state i.year , r  

Iteration 0:   log pseudolikelihood =  -7481.795  
Iteration 1:   log pseudolikelihood = -7013.2394  
Iteration 2:   log pseudolikelihood =  -7007.445  
Iteration 3:   log pseudolikelihood = -7007.4339  
Iteration 4:   log pseudolikelihood = -7007.4339  

Ordered logistic regression                     Number of obs     =      5,773
                                                Wald chi2(97)     =     876.65
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -7007.4339               Pseudo R2         =     0.0634

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_20a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.2193995    .071388    -3.07   0.002    -.3593174   -.0794817
                     Man of Color  |   .1952812   .1048834     1.86   0.063    -.0102864    .4008489
                   Woman of Color  |   .4904393   .1949114     2.52   0.012     .1084199    .8724586
                                   |
                           reve_1a |
                Less than Monthly  |    .237459   .0798742     2.97   0.003     .0809084    .3940097
                          Monthly  |   .2854431   .1010281     2.83   0.005     .0874316    .4834546
                           Weekly  |   .4267662   .1230623     3.47   0.001     .1855686    .6679638
                            Daily  |   .5604197   .2328336     2.41   0.016     .1040743    1.016765
                                   |
                           reve_1b |
                Less than Monthly  |   .2583652   .1993266     1.30   0.195    -.1323077    .6490381
                          Monthly  |   .4155491   .2042042     2.03   0.042     .0153163     .815782
                           Weekly  |   .6677943   .2074512     3.22   0.001     .2611974    1.074391
                            Daily  |   .9182033   .2191347     4.19   0.000     .4887072    1.347699
                                   |
                     civil_service |
                              Yes  |   .2147266   .0660189     3.25   0.001      .085332    .3441212
                      weekly_hours |  -.0032919   .0032998    -1.00   0.318    -.0097594    .0031755
                               age |  -.0384093   .0242508    -1.58   0.113      -.08594    .0091215
                             age_2 |   .0003158   .0002398     1.32   0.188    -.0001542    .0007858
                                   |
                               edu |
              High school or less  |   .3435001    .269791     1.27   0.203    -.1852805    .8722806
                     Some college  |  -.0680177   .1322972    -0.51   0.607    -.3273155    .1912801
                   Graduate study  |  -.0220982     .08832    -0.25   0.802    -.1952023    .1510059
                  Graduate degree  |  -.2281793   .0717697    -3.18   0.001    -.3688454   -.0875132
                                   |
                years_employ_state |  -.0015395   .0043654    -0.35   0.724    -.0100955    .0070165
               years_employ_agency |   .0017306   .0046197     0.37   0.708    -.0073238     .010785
             years_employ_position |  -.0281099   .0063413    -4.43   0.000    -.0405386   -.0156813
                                   |
                              pid5 |
                       Republican  |   .1277801   .0897239     1.42   0.154    -.0480756    .3036358
                  Lean Republican  |     .10112   .1144743     0.88   0.377    -.1232455    .3254854
                  Lean Democratic  |   .1099132   .1046238     1.05   0.293    -.0951458    .3149721
                       Democratic  |   .1054323   .0820166     1.29   0.199    -.0553171    .2661818
                                   |
                       agency_size |
                           25-100  |  -.1017669   .0845669    -1.20   0.229     -.267515    .0639812
                          101-500  |  -.2534404   .0917565    -2.76   0.006    -.4332797    -.073601
                        501-1,000  |  -.3924013   .1163281    -3.37   0.001    -.6204001   -.1644024
                      1,001-5,000  |  -.4494825   .1219669    -3.69   0.000    -.6885332   -.2104317
                       Over 5,000  |  -.4432998   .1610766    -2.75   0.006    -.7590042   -.1275954
                                   |
                 log_agency_budget |  -.0018832    .020022    -0.09   0.925    -.0411257    .0373593
                      inst6017_nom |  -.0033845   .0030619    -1.11   0.269    -.0093857    .0026167
                                   |
                          funcat13 |
                    Staff: Fiscal  |   2.215103   .1877377    11.80   0.000     1.847144    2.583062
                Staff: Non-Fiscal  |   2.508415   .1879715    13.34   0.000     2.139997    2.876832
Income Security & Social Services  |   1.905784   .1747725    10.90   0.000     1.563237    2.248332
                        Education  |   1.525621   .1840071     8.29   0.000     1.164974    1.886268
                           Health  |   1.931413   .1841468    10.49   0.000     1.570492    2.292334
                Natural Resources  |   1.713114   .1663994    10.30   0.000     1.386977     2.03925
             Environment & Energy  |   1.771442   .1721321    10.29   0.000     1.434069    2.108815
             Economic Development  |   1.778946   .1790369     9.94   0.000      1.42804    2.129852
                 Criminal Justice  |   1.784371   .1764269    10.11   0.000      1.43858    2.130161
                       Regulatory  |    1.25871   .1672022     7.53   0.000     .9309997     1.58642
                   Transportation  |   1.871534   .1866036    10.03   0.000     1.505797     2.23727
                            Other  |   1.816414   .1801567    10.08   0.000     1.463313    2.169514
                                   |
                             state |
                               AK  |   1.060618   .2506041     4.23   0.000     .5694429    1.551793
                               AZ  |   .5340939   .2676427     2.00   0.046     .0095238    1.058664
                               AR  |   .7353661   .2595793     2.83   0.005        .2266    1.244132
                               CA  |   1.203706   .3003642     4.01   0.000     .6150034    1.792409
                               CO  |  -.5071488   .2458765    -2.06   0.039    -.9890578   -.0252397
                               CT  |   .3869609   .3042153     1.27   0.203    -.2092901    .9832119
                               DE  |   .4611498   .2402465     1.92   0.055    -.0097247    .9320243
                               FL  |   .5951544    .257098     2.31   0.021     .0912516    1.099057
                               GA  |   .5578938   .2453903     2.27   0.023     .0769377     1.03885
                               HI  |     1.1981   .2607096     4.60   0.000     .6871184    1.709081
                               ID  |   .2350182   .2481279     0.95   0.344    -.2513035    .7213399
                               IL  |   .7064442   .2825175     2.50   0.012     .1527201    1.260168
                               IN  |   1.334604   .2513236     5.31   0.000     .8420184    1.827189
                               IA  |   .5397787    .229333     2.35   0.019     .0902943    .9892631
                               KS  |   .4908527   .2629437     1.87   0.062    -.0245074    1.006213
                               KY  |   1.227621   .2645671     4.64   0.000     .7090792    1.746163
                               LA  |    .591033   .2646067     2.23   0.026     .0724134    1.109653
                               ME  |   .0181882   .2554409     0.07   0.943    -.4824666    .5188431
                               MD  |   .5867544   .2596833     2.26   0.024     .0777845    1.095724
                               MA  |   .8714516    .283558     3.07   0.002     .3156882    1.427215
                               MI  |    .973911   .2488842     3.91   0.000      .486107    1.461715
                               MN  |  -.0120383   .2341248    -0.05   0.959    -.4709145     .446838
                               MS  |  -.3410558   .2710853    -1.26   0.208    -.8723733    .1902617
                               MO  |    .364905   .2398716     1.52   0.128    -.1052348    .8350448
                               MT  |   .1672763   .2404772     0.70   0.487    -.3040504     .638603
                               NV  |   .5455663   .2439758     2.24   0.025     .0673826     1.02375
                               NH  |   .0524166    .256247     0.20   0.838    -.4498182    .5546515
                               NJ  |    1.25406   .2690022     4.66   0.000     .7268252    1.781295
                               NM  |   .3834404   .2599468     1.48   0.140     -.126046    .8929268
                               NY  |   1.200913   .2954115     4.07   0.000     .6219167    1.779908
                               NC  |    .494924   .2307998     2.14   0.032     .0425646    .9472833
                               OH  |   .6229094   .2368185     2.63   0.009     .1587536    1.087065
                               OK  |   .7047984   .2536457     2.78   0.005      .207662    1.201935
                               OR  |   .2248942   .2341349     0.96   0.337    -.2340017    .6837901
                               PA  |   1.308378   .2497434     5.24   0.000     .8188899    1.797866
                               RI  |   .5380589   .2639669     2.04   0.042     .0206933    1.055425
                               SC  |   .0517439   .2460686     0.21   0.833    -.4305417    .5340295
                               SD  |   .5735413   .2462672     2.33   0.020     .0908664    1.056216
                               TN  |   .9482366   .2633079     3.60   0.000     .4321626    1.464311
                               TX  |  -.0966745   .2562802    -0.38   0.706    -.5989746    .4056255
                               UT  |   .6411652    .232472     2.76   0.006     .1855285    1.096802
                               VA  |   1.267869   .2746532     4.62   0.000     .7295588    1.806179
                               WA  |    .327684   .2485898     1.32   0.187    -.1595431    .8149112
                               WV  |   .4434391   .2480829     1.79   0.074    -.0427945    .9296727
                               WI  |   .7243024   .2338904     3.10   0.002     .2658856    1.182719
                               WY  |   .8248885   .2536772     3.25   0.001     .3276904    1.322087
                                   |
                              year |
                             1984  |  -.0940463   .1006543    -0.93   0.350    -.2913252    .1032326
                             1988  |  -.2086954   .0973025    -2.14   0.032    -.3994047   -.0179861
                             1994  |   .2482083   .1024351     2.42   0.015     .0474392    .4489774
                             1998  |   .4211395   .1066195     3.95   0.000     .2121692    .6301098
                             2004  |  -.0537335   .1093921    -0.49   0.623    -.2681381     .160671
                             2008  |   .2866759   .1150286     2.49   0.013     .0612239    .5121278
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.321561   .6751981                     -2.644925     .001803
                             /cut2 |   .8524217   .6744581                     -.4694919    2.174335
                             /cut3 |   2.337752   .6749344                      1.014905    3.660599
----------------------------------------------------------------------------------------------------

. est sto b7

. ologit d_21a i.intersection i.reve_1c i.reve_1d i.civil_service weekly_hours age age_2 b3.edu years_employ_
> state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fun
> cat13 i.state i.year , r 

Iteration 0:   log pseudolikelihood = -7197.6747  
Iteration 1:   log pseudolikelihood = -6975.7215  
Iteration 2:   log pseudolikelihood = -6974.5753  
Iteration 3:   log pseudolikelihood = -6974.5748  

Ordered logistic regression                     Number of obs     =      5,759
                                                Wald chi2(97)     =     420.83
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -6974.5748               Pseudo R2         =     0.0310

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_21a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.0789517   .0705371    -1.12   0.263    -.2172018    .0592984
                     Man of Color  |    .374313   .0982475     3.81   0.000     .1817515    .5668746
                   Woman of Color  |   .5877034   .2015554     2.92   0.004      .192662    .9827448
                                   |
                           reve_1c |
                Less than Monthly  |   .0597028   .2849275     0.21   0.834    -.4987448    .6181503
                          Monthly  |  -.0483463   .2868431    -0.17   0.866    -.6105484    .5138558
                           Weekly  |   .0360566   .2911054     0.12   0.901    -.5344996    .6066128
                            Daily  |  -.0090301   .3054981    -0.03   0.976    -.6077955    .5897352
                                   |
                           reve_1d |
                Less than Monthly  |   .8507086   .2317878     3.67   0.000     .3964129    1.305004
                          Monthly  |   1.039481   .2324647     4.47   0.000     .5838581    1.495103
                           Weekly  |   1.132652   .2355586     4.81   0.000     .6709657    1.594338
                            Daily  |    1.35817   .2533717     5.36   0.000     .8615704    1.854769
                                   |
                     civil_service |
                              Yes  |   .1002263   .0652499     1.54   0.125    -.0276613    .2281138
                      weekly_hours |   .0005197   .0032607     0.16   0.873    -.0058711    .0069106
                               age |  -.0334353   .0256905    -1.30   0.193    -.0837877    .0169171
                             age_2 |   .0003737   .0002558     1.46   0.144    -.0001277    .0008751
                                   |
                               edu |
              High school or less  |   .3977383   .2827596     1.41   0.160    -.1564604     .951937
                     Some college  |   -.234126   .1306639    -1.79   0.073    -.4902225    .0219705
                   Graduate study  |  -.1306602   .0893831    -1.46   0.144    -.3058479    .0445275
                  Graduate degree  |   -.252175    .070456    -3.58   0.000    -.3902662   -.1140839
                                   |
                years_employ_state |  -.0072985   .0041055    -1.78   0.075    -.0153452    .0007483
               years_employ_agency |   .0075911   .0044127     1.72   0.085    -.0010576    .0162397
             years_employ_position |  -.0178948   .0066881    -2.68   0.007    -.0310032   -.0047864
                                   |
                              pid5 |
                       Republican  |  -.0679176   .0910128    -0.75   0.456    -.2462993    .1104642
                  Lean Republican  |   .0604114    .115016     0.53   0.599    -.1650158    .2858386
                  Lean Democratic  |    .066638    .106814     0.62   0.533    -.1427135    .2759895
                       Democratic  |  -.0370526   .0828103    -0.45   0.655    -.1993578    .1252525
                                   |
                       agency_size |
                           25-100  |   .1132665   .0859968     1.32   0.188    -.0552841    .2818171
                          101-500  |   .1307655     .09369     1.40   0.163    -.0528635    .3143944
                        501-1,000  |  -.0862238   .1165899    -0.74   0.460    -.3147357    .1422881
                      1,001-5,000  |  -.0684304   .1216601    -0.56   0.574    -.3068798    .1700191
                       Over 5,000  |  -.1134106   .1604665    -0.71   0.480    -.4279192     .201098
                                   |
                 log_agency_budget |   .0175304   .0203296     0.86   0.389    -.0223149    .0573756
                      inst6017_nom |   .0044996   .0031153     1.44   0.149    -.0016064    .0106055
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .1753684   .1863616     0.94   0.347    -.1898936    .5406303
                Staff: Non-Fiscal  |   .2537861   .1955264     1.30   0.194    -.1294386    .6370107
Income Security & Social Services  |   .0968938   .1783664     0.54   0.587    -.2526979    .4464856
                        Education  |   .1078481   .1874049     0.58   0.565    -.2594587    .4751549
                           Health  |   .2981162   .1845968     1.61   0.106    -.0636868    .6599193
                Natural Resources  |    .328894   .1699488     1.94   0.053    -.0041994    .6619875
             Environment & Energy  |   .3942275   .1766045     2.23   0.026      .048089    .7403661
             Economic Development  |   .0549228    .181084     0.30   0.762    -.2999953     .409841
                 Criminal Justice  |  -.0735003   .1830797    -0.40   0.688    -.4323299    .2853292
                       Regulatory  |   .0078814   .1716765     0.05   0.963    -.3285983    .3443611
                   Transportation  |   .3722566   .1894064     1.97   0.049     .0010268    .7434864
                            Other  |   .2150844   .1816634     1.18   0.236    -.1409693    .5711381
                                   |
                             state |
                               AK  |   .1144613   .2282522     0.50   0.616    -.3329047    .5618274
                               AZ  |   .1423829   .2546747     0.56   0.576    -.3567704    .6415361
                               AR  |   .7556208   .2468631     3.06   0.002     .2717781    1.239464
                               CA  |   .1421709   .2530724     0.56   0.574    -.3538418    .6381837
                               CO  |  -.0018226   .2314804    -0.01   0.994    -.4555159    .4518707
                               CT  |   .8741202   .2995738     2.92   0.004     .2869663    1.461274
                               DE  |   .2093814   .2339435     0.90   0.371    -.2491394    .6679022
                               FL  |    .553753    .254923     2.17   0.030     .0541131    1.053393
                               GA  |   .2321441   .2367737     0.98   0.327    -.2319238    .6962121
                               HI  |  -.3292944   .2512362    -1.31   0.190    -.8217084    .1631196
                               ID  |    .831995   .2362943     3.52   0.000     .3688666    1.295123
                               IL  |   .3267093   .2560356     1.28   0.202    -.1751112    .8285297
                               IN  |   .2349226    .245628     0.96   0.339    -.2464993    .7163446
                               IA  |    .894418   .2138791     4.18   0.000     .4752226    1.313613
                               KS  |    .993923   .2451459     4.05   0.000      .513446      1.4744
                               KY  |   1.003165   .2386636     4.20   0.000      .535393    1.470937
                               LA  |   .4273842   .2577519     1.66   0.097    -.0778002    .9325687
                               ME  |   .2655669   .2538334     1.05   0.295    -.2319375    .7630713
                               MD  |    .615737   .2453079     2.51   0.012     .1349422    1.096532
                               MA  |  -.1762992   .2374081    -0.74   0.458    -.6416105     .289012
                               MI  |   .9078168   .2381486     3.81   0.000     .4410541    1.374579
                               MN  |   .0545129   .2231596     0.24   0.807    -.3828718    .4918976
                               MS  |   .4533706   .2489964     1.82   0.069    -.0346534    .9413947
                               MO  |   .2224156   .2222752     1.00   0.317    -.2132358    .6580669
                               MT  |   .0385636    .222216     0.17   0.862    -.3969718    .4740989
                               NV  |   .3757497   .2429065     1.55   0.122    -.1003382    .8518377
                               NH  |   1.107459   .2521291     4.39   0.000     .6132949    1.601623
                               NJ  |   .4359015   .2562013     1.70   0.089    -.0662438    .9380468
                               NM  |  -.3887469     .24771    -1.57   0.117    -.8742495    .0967557
                               NY  |   .1847112   .2828822     0.65   0.514    -.3697276    .7391501
                               NC  |    .428035   .2261842     1.89   0.058     -.015278    .8713479
                               OH  |   .6500725   .2363256     2.75   0.006     .1868829    1.113262
                               OK  |   .8221315   .2350796     3.50   0.000      .361384    1.282879
                               OR  |   .0759244   .2268357     0.33   0.738    -.3686655    .5205143
                               PA  |   .2136618    .244357     0.87   0.382    -.2652691    .6925928
                               RI  |   .0328871   .2453091     0.13   0.893      -.44791    .5136842
                               SC  |   1.093035   .2814689     3.88   0.000      .541366    1.644704
                               SD  |   .2179818   .2548321     0.86   0.392    -.2814799    .7174435
                               TN  |    .818079    .241594     3.39   0.001     .3445634    1.291595
                               TX  |   .6334392   .2599295     2.44   0.015     .1239868    1.142892
                               UT  |   .4831292   .2242714     2.15   0.031     .0435652    .9226931
                               VA  |   .3771725   .2709965     1.39   0.164    -.1539709    .9083159
                               WA  |  -.1601897   .2277591    -0.70   0.482    -.6065893    .2862099
                               WV  |   1.073331   .2430824     4.42   0.000     .5968981    1.549764
                               WI  |   .8389895   .2231367     3.76   0.000     .4016497    1.276329
                               WY  |   .4186461   .2350392     1.78   0.075    -.0420223    .8793145
                                   |
                              year |
                             1984  |  -.1966623    .096718    -2.03   0.042    -.3862261   -.0070986
                             1988  |   -.157758   .0948304    -1.66   0.096    -.3436221    .0281062
                             1994  |   .0677462   .0975818     0.69   0.488    -.1235106     .259003
                             1998  |   .2519374   .1045657     2.41   0.016     .0469924    .4568824
                             2004  |  -.1768364   .1104996    -1.60   0.110    -.3934116    .0397389
                             2008  |   .2253374   .1149117     1.96   0.050     .0001147    .4505601
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.875202   .7758051                     -3.395752   -.3546519
                             /cut2 |   .4619515   .7721399                     -1.051415    1.975318
                             /cut3 |   2.116634   .7720573                      .6034294    3.629838
----------------------------------------------------------------------------------------------------

. est sto b8 

.  
.  esttab b1 b2 b3 b4 b5 b6 b7 b8 using Table_B3.rtf ,starlevels(+ 0.10 * 0.05 ** 0.01) cells(b(star fmt(3)) 
> se(par fmt(3))) ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Gov. Policy" "Legis. Policy" "Gov. Regs" "Legis. Regs" "Gov. Policy" "Legis. Policy" "Gov. Regs" 
> "Legis. Regs") 
(output written to Table_B3.rtf)

. 
. clear all

. ***** RE-RUN PREAMBLE ***** 
. use par_asap.dta

. 
. gen intersection=0 if k_4a==1 & k_3a==1
(4,393 missing values generated)

. replace intersection=1 if k_4a==1 & k_3a==2
(1,306 real changes made)

. replace intersection=2 if  k_4a==0 & k_3a==1
(660 real changes made)

. replace intersection=3 if  k_4a==0 & k_3a==2
(188 real changes made)

. 
. label define mintersection 0"White Man"  1"White Woman" 2"Man of Color" 3"Woman of Color"

. 
. label value intersection mintersection

. 
. 
. rename a_2a civil_service 

. label var civil_service "Civil Servant"

. rename a_8a weekly_hours

. label var weekly_hours "Average Weekley Hours Worked"

. rename j_1a years_employ_state

. label var years_employ_state  "Years Employed in State Gov."

. rename j_1b years_employ_agency

. label var years_employ_agency  "Years Employed in Agency"

. rename j_1c years_employ_position 

. label var years_employ_position  "Years Employed in Position"

. gen age_2 = k_2a*k_2a
(490 missing values generated)

. label var age_2 "Age-squared"

. gen age = sqrt(age_2)
(490 missing values generated)

. label var age "Age"

. gen pid5= 1 if k_8b==2
(9,130 missing values generated)

. replace pid5= 2 if k_8b==4
(748 real changes made)

. replace pid5= 3 if k_8b==5
(1,210 real changes made)

. replace pid5= 4 if k_8b==3
(868 real changes made)

. replace pid5= 5 if k_8b==1
(3,880 real changes made)

. label var pid5 "Party ID"

. label define mpid5 1"Republican"  2"Lean Republican" 3"Independant" 4"Lean Democratic" 5"Democratic"

. 
. label value pid5 mpid5

. 
. 
. rename k_16a edu

. label var edu "Education"

. 
. rename a_3b agency_size

. label var agency_size "Total Agency Employees"

. 
. rename a_4b agency_budget 

. gen log_agency_budget = ln(1+agency_budget) 
(773 missing values generated)

. label var log_agency_budget "ln(Agency Budget, $2018)"

. 
. revrs e_1a 

. revrs e_1b 

. revrs e_1c 

. revrs e_1d 

. 
. label var reve_1a "Gov."

. label var reve_1b "Gov. Staff"

. label var reve_1c "Legis."

. label var reve_1d "Legis. Staff"

. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B4 ******
. ologit reve_1a i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r if state!= 11 , r 

Iteration 0:   log pseudolikelihood = -10155.838  
Iteration 1:   log pseudolikelihood = -8655.4236  
Iteration 2:   log pseudolikelihood = -8587.1882  
Iteration 3:   log pseudolikelihood =  -8587.048  
Iteration 4:   log pseudolikelihood =  -8587.048  

Ordered logistic regression                     Number of obs     =      7,371
                                                Wald chi2(92)     =    2806.60
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -8587.048               Pseudo R2         =     0.1545

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.2326117   .0711145    -3.27   0.001    -.3719935   -.0932298
                     Man of Color  |   -.138792   .1053863    -1.32   0.188    -.3453453    .0677614
                   Woman of Color  |  -.4667004   .1713882    -2.72   0.006     -.802615   -.1307857
                                   |
                     civil_service |
                              Yes  |  -.9668622   .0608248   -15.90   0.000    -1.086077   -.8476478
                      weekly_hours |   .0521579   .0031548    16.53   0.000     .0459745    .0583413
                               age |  -.0318141   .0225563    -1.41   0.158    -.0760236    .0123954
                             age_2 |   .0004733   .0002224     2.13   0.033     .0000375    .0009091
                                   |
                               edu |
              High school or less  |   .0259593   .1985563     0.13   0.896     -.363204    .4151226
                     Some college  |   .1056444     .10662     0.99   0.322     -.103327    .3146157
                   Graduate study  |   .0545486   .0780081     0.70   0.484    -.0983445    .2074417
                  Graduate degree  |  -.1008501   .0654185    -1.54   0.123     -.229068    .0273679
                                   |
                years_employ_state |   .0004858   .0041967     0.12   0.908    -.0077395    .0087112
               years_employ_agency |  -.0314441   .0044178    -7.12   0.000    -.0401029   -.0227854
             years_employ_position |   .0086388   .0055646     1.55   0.121    -.0022676    .0195453
                                   |
                              pid5 |
                       Republican  |   .4981872   .0826269     6.03   0.000     .3362415     .660133
                  Lean Republican  |   .1434552   .1023415     1.40   0.161    -.0571305    .3440408
                  Lean Democratic  |  -.0212243   .0986384    -0.22   0.830     -.214552    .1721034
                       Democratic  |   .5004051   .0756883     6.61   0.000     .3520586    .6487515
                                   |
                       agency_size |
                           25-100  |   .1718123   .0737719     2.33   0.020      .027222    .3164026
                          101-500  |   .5125574   .0847698     6.05   0.000     .3464117    .6787031
                        501-1,000  |   .7627069   .1124286     6.78   0.000     .5423509     .983063
                      1,001-5,000  |   1.067151   .1159568     9.20   0.000     .8398801    1.294422
                       Over 5,000  |   1.512862   .1560934     9.69   0.000     1.206925      1.8188
                                   |
                 log_agency_budget |   .1741563   .0201316     8.65   0.000      .134699    .2136136
                      inst6017_nom |  -.0032781   .0028512    -1.15   0.250    -.0088664    .0023101
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .7190639   .1633187     4.40   0.000     .3989652    1.039163
                Staff: Non-Fiscal  |  -.2285993   .1587851    -1.44   0.150    -.5398124    .0826137
Income Security & Social Services  |  -1.458258   .1378932   -10.58   0.000    -1.728524   -1.187993
                        Education  |  -.9445439   .1468249    -6.43   0.000    -1.232316   -.6567723
                           Health  |  -1.646001   .1483523   -11.10   0.000    -1.936767   -1.355236
                Natural Resources  |  -.7733111   .1266729    -6.10   0.000    -1.021586   -.5250367
             Environment & Energy  |  -.7742848    .135539    -5.71   0.000    -1.039936   -.5086333
             Economic Development  |   .0518231   .1393838     0.37   0.710    -.2213642    .3250104
                 Criminal Justice  |  -.9391747   .1357065    -6.92   0.000    -1.205155   -.6731948
                       Regulatory  |  -1.253412   .1311814    -9.55   0.000    -1.510523   -.9963013
                   Transportation  |  -.9762625   .1417703    -6.89   0.000    -1.254127   -.6983978
                            Other  |  -.7390476   .1373696    -5.38   0.000    -1.008287   -.4698082
                                   |
                             state |
                               AK  |  -.3322584      .2203    -1.51   0.132    -.7640385    .0995217
                               AZ  |  -1.071945    .245964    -4.36   0.000    -1.554025   -.5898638
                               AR  |   -.229034   .2041714    -1.12   0.262    -.6292027    .1711346
                               CA  |  -2.499169   .2443442   -10.23   0.000    -2.978075   -2.020263
                               CO  |  -.0356055   .2135049    -0.17   0.868    -.4540674    .3828563
                               CT  |  -1.155485    .252374    -4.58   0.000    -1.650129   -.6608413
                               DE  |   -.370931   .2117278    -1.75   0.080    -.7859098    .0440478
                               FL  |  -1.692188   .2441932    -6.93   0.000    -2.170797   -1.213578
                               GA  |   -.923931   .2312366    -4.00   0.000    -1.377146   -.4707157
                               ID  |   .2403953   .2054585     1.17   0.242     -.162296    .6430867
                               IL  |  -1.428263   .2446614    -5.84   0.000     -1.90779    -.948735
                               IN  |   -.572599   .2312978    -2.48   0.013    -1.025934   -.1192637
                               IA  |  -.2832508   .1989509    -1.42   0.155    -.6731874    .1066859
                               KS  |   -.405711   .2281956    -1.78   0.075    -.8529662    .0415441
                               KY  |  -1.066803   .2295096    -4.65   0.000    -1.516634   -.6169726
                               LA  |  -.8228811   .2612731    -3.15   0.002    -1.334967   -.3107954
                               ME  |  -.0775132   .2262045    -0.34   0.732    -.5208658    .3658395
                               MD  |  -.9908327    .232414    -4.26   0.000    -1.446356   -.5353097
                               MA  |  -1.684712   .2455231    -6.86   0.000    -2.165929   -1.203496
                               MI  |  -.8763405   .2182139    -4.02   0.000    -1.304032   -.4486492
                               MN  |  -1.106893   .2260387    -4.90   0.000     -1.54992   -.6638649
                               MS  |  -.2830722    .225435    -1.26   0.209    -.7249166    .1587722
                               MO  |  -1.219421     .21378    -5.70   0.000    -1.638422   -.8004198
                               MT  |   .1305761    .202002     0.65   0.518    -.2653405    .5264927
                               NE  |   .1833033   .2294875     0.80   0.424     -.266484    .6330906
                               NV  |  -.2411787   .2127682    -1.13   0.257    -.6581968    .1758394
                               NH  |  -.0719891   .2232332    -0.32   0.747    -.5095181      .36554
                               NJ  |  -1.229406   .2333237    -5.27   0.000    -1.686712   -.7720997
                               NM  |   .0452105   .2279935     0.20   0.843    -.4016486    .4920696
                               NY  |  -2.187971   .2691049    -8.13   0.000    -2.715407   -1.660535
                               NC  |  -1.040918   .1962626    -5.30   0.000    -1.425586   -.6562502
                               ND  |   .6589338   .2065085     3.19   0.001     .2541845    1.063683
                               OH  |  -1.235295   .2367176    -5.22   0.000    -1.699253   -.7713369
                               OK  |  -.6736967    .215891    -3.12   0.002    -1.096835   -.2505581
                               OR  |  -.2763225   .2184998    -1.26   0.206    -.7045743    .1519293
                               PA  |  -1.881144   .2286513    -8.23   0.000    -2.329292   -1.432995
                               RI  |   .2179746   .2272624     0.96   0.337    -.2274515    .6634007
                               SC  |  -.5543814   .2142771    -2.59   0.010    -.9743567    -.134406
                               SD  |   .3475864   .2143833     1.62   0.105    -.0725971    .7677699
                               TN  |  -1.180386   .2333571    -5.06   0.000    -1.637758   -.7230148
                               TX  |  -1.982322    .215792    -9.19   0.000    -2.405266   -1.559377
                               UT  |   .0435997   .2042072     0.21   0.831     -.356639    .4438385
                               VT  |   .2676527   .2118442     1.26   0.206    -.1475542    .6828597
                               VA  |  -1.116398   .2327893    -4.80   0.000    -1.572657   -.6601396
                               WA  |  -.9931023   .2307858    -4.30   0.000    -1.445434   -.5407703
                               WV  |  -.5096708   .2181344    -2.34   0.019    -.9372064   -.0821351
                               WI  |   -.443286   .2168825    -2.04   0.041    -.8683679   -.0182042
                               WY  |   .5407455    .196253     2.76   0.006     .1560966    .9253944
                                   |
                              year |
                             1978  |  -.6641967   .0883603    -7.52   0.000    -.8373798   -.4910136
                             1984  |  -.6643553   .0847049    -7.84   0.000    -.8303738   -.4983368
                             1988  |   -.982513   .0803032   -12.24   0.000    -1.139904   -.8251217
                             1994  |  -.8431902   .0860745    -9.80   0.000    -1.011893   -.6744872
                             1998  |  -1.184953   .0933005   -12.70   0.000    -1.367819   -1.002087
                             2004  |  -1.228027   .0959079   -12.80   0.000    -1.416003   -1.040051
                             2008  |  -1.520211   .1220886   -12.45   0.000      -1.7595   -1.280922
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.345167   .6261005                     -2.572301   -.1180324
                             /cut2 |   1.301964   .6255035                      .0759992    2.527928
                             /cut3 |   2.780588   .6268335                      1.552017    4.009159
                             /cut4 |   5.296163   .6352882                      4.051021    6.541305
----------------------------------------------------------------------------------------------------

. est sto c1

. ologit reve_1b i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r if state!= 11 , r 

Iteration 0:   log pseudolikelihood = -8993.9072  
Iteration 1:   log pseudolikelihood = -7928.0448  
Iteration 2:   log pseudolikelihood = -7901.6756  
Iteration 3:   log pseudolikelihood = -7901.6334  
Iteration 4:   log pseudolikelihood = -7901.6334  

Ordered logistic regression                     Number of obs     =      6,251
                                                Wald chi2(91)     =    1959.66
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -7901.6334               Pseudo R2         =     0.1214

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1b |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.1492132   .0670139    -2.23   0.026    -.2805581   -.0178683
                     Man of Color  |  -.0649889   .1068649    -0.61   0.543    -.2744402    .1444624
                   Woman of Color  |  -.4916028    .177279    -2.77   0.006    -.8390632   -.1441423
                                   |
                     civil_service |
                              Yes  |  -.8057191   .0614662   -13.11   0.000    -.9261907   -.6852475
                      weekly_hours |   .0480778   .0033937    14.17   0.000     .0414263    .0547293
                               age |  -.0725539   .0232947    -3.11   0.002    -.1182107    -.026897
                             age_2 |   .0006567    .000229     2.87   0.004     .0002078    .0011055
                                   |
                               edu |
              High school or less  |   .2625683   .2273773     1.15   0.248     -.183083    .7082195
                     Some college  |   .1589289   .1194186     1.33   0.183    -.0751273    .3929851
                   Graduate study  |   .1520514   .0832748     1.83   0.068    -.0111643    .3152671
                  Graduate degree  |   .0691883   .0696564     0.99   0.321    -.0673358    .2057123
                                   |
                years_employ_state |   .0066409   .0043088     1.54   0.123    -.0018042    .0150861
               years_employ_agency |  -.0290368   .0045034    -6.45   0.000    -.0378634   -.0202102
             years_employ_position |  -.0058141   .0060408    -0.96   0.336    -.0176538    .0060256
                                   |
                              pid5 |
                       Republican  |    .393938   .0857872     4.59   0.000     .2257982    .5620779
                  Lean Republican  |   .0472511   .1084868     0.44   0.663    -.1653791    .2598813
                  Lean Democratic  |  -.0491316   .0979288    -0.50   0.616    -.2410685    .1428052
                       Democratic  |   .3473684   .0803194     4.32   0.000     .1899453    .5047915
                                   |
                       agency_size |
                           25-100  |  -.0273506   .0794261    -0.34   0.731     -.183023    .1283217
                          101-500  |   .2060023   .0904618     2.28   0.023     .0287005    .3833042
                        501-1,000  |   .3552511   .1212589     2.93   0.003     .1175879    .5929142
                      1,001-5,000  |   .6437221   .1261889     5.10   0.000     .3963964    .8910478
                       Over 5,000  |    1.06351    .172129     6.18   0.000      .726143    1.400876
                                   |
                 log_agency_budget |   .1838592     .02168     8.48   0.000     .1413672    .2263512
                      inst6017_nom |   .0029224   .0031524     0.93   0.354    -.0032562    .0091009
                                   |
                          funcat13 |
                    Staff: Fiscal  |   1.431957   .1775773     8.06   0.000     1.083912    1.780002
                Staff: Non-Fiscal  |   .9610715   .1866238     5.15   0.000     .5952955    1.326847
Income Security & Social Services  |  -.4398716   .1525354    -2.88   0.004    -.7388355   -.1409077
                        Education  |  -.3683816   .1620297    -2.27   0.023     -.685954   -.0508092
                           Health  |  -.6015103   .1602818    -3.75   0.000    -.9156569   -.2873637
                Natural Resources  |  -.0772665   .1442434    -0.54   0.592    -.3599783    .2054453
             Environment & Energy  |   .0453716   .1499522     0.30   0.762    -.2485293    .3392725
             Economic Development  |   .7898377    .153093     5.16   0.000     .4897808    1.089894
                 Criminal Justice  |   .0322691    .153521     0.21   0.834    -.2686266    .3331647
                       Regulatory  |  -.6237374   .1440042    -4.33   0.000    -.9059804   -.3414943
                   Transportation  |  -.1758016   .1607541    -1.09   0.274    -.4908739    .1392707
                            Other  |   .1612117   .1525104     1.06   0.290    -.1377031    .4601265
                                   |
                             state |
                               AK  |  -.0749618   .2332425    -0.32   0.748    -.5321087    .3821851
                               AZ  |  -.3707641   .2398387    -1.55   0.122    -.8408394    .0993111
                               AR  |   .3353758   .2255948     1.49   0.137     -.106782    .7775335
                               CA  |   -1.53405   .2570951    -5.97   0.000    -2.037947   -1.030153
                               CO  |  -.2672663   .2257963    -1.18   0.237    -.7098191    .1752864
                               CT  |  -.8231784    .266835    -3.08   0.002    -1.346165   -.3001915
                               DE  |  -.8593734   .2253635    -3.81   0.000    -1.301078    -.417669
                               FL  |   -1.32574   .2398119    -5.53   0.000    -1.795762   -.8557168
                               GA  |  -.8175013   .2571195    -3.18   0.001    -1.321446   -.3135564
                               ID  |   .7278361   .2244089     3.24   0.001     .2880028    1.167669
                               IL  |   -.389187   .2893267    -1.35   0.179    -.9562568    .1778829
                               IN  |   .1275745   .2345068     0.54   0.586    -.3320504    .5871994
                               IA  |  -.3082571   .2213612    -1.39   0.164    -.7421171     .125603
                               KS  |  -.5510671   .2274156    -2.42   0.015    -.9967934   -.1053407
                               KY  |  -.8217248   .2381292    -3.45   0.001    -1.288449       -.355
                               LA  |  -.3501869   .2503491    -1.40   0.162    -.8408622    .1404884
                               ME  |   .1846776   .2455179     0.75   0.452    -.2965286    .6658838
                               MD  |  -.4417348   .2373003    -1.86   0.063    -.9068347    .0233652
                               MA  |  -1.064471    .267774    -3.98   0.000    -1.589298   -.5396433
                               MI  |  -.3458894   .2372391    -1.46   0.145    -.8108695    .1190907
                               MN  |  -.9806686   .2262611    -4.33   0.000    -1.424132    -.537205
                               MS  |   -.567995   .2500715    -2.27   0.023    -1.058126   -.0778639
                               MO  |  -1.093691    .232523    -4.70   0.000    -1.549427    -.637954
                               MT  |   .1651568   .2052529     0.80   0.421    -.2371315    .5674451
                               NE  |  -.2376285   .2261941    -1.05   0.293    -.6809609    .2057038
                               NV  |  -.2600095   .2275861    -1.14   0.253    -.7060702    .1860511
                               NH  |   .0695004   .2423125     0.29   0.774    -.4054234    .5444242
                               NJ  |  -.8366416   .2595619    -3.22   0.001    -1.345374   -.3279096
                               NM  |  -.2600535   .2356728    -1.10   0.270    -.7219637    .2018566
                               NY  |  -.1974998   .3047803    -0.65   0.517    -.7948582    .3998587
                               NC  |  -.9638758   .2165652    -4.45   0.000    -1.388336   -.5394158
                               ND  |   .2203089   .2060121     1.07   0.285    -.1834674    .6240853
                               OH  |  -.9530915   .2365949    -4.03   0.000    -1.416809    -.489374
                               OK  |  -.8038215   .2283982    -3.52   0.000    -1.251474   -.3561692
                               OR  |  -.3180109   .2253949    -1.41   0.158    -.7597768    .1237551
                               PA  |  -1.466891   .2578619    -5.69   0.000    -1.972292   -.9614913
                               RI  |   .3999707   .2412616     1.66   0.097    -.0728933    .8728346
                               SC  |  -.4384041   .2327516    -1.88   0.060    -.8945889    .0177808
                               SD  |   .0798529   .2284559     0.35   0.727    -.3679125    .5276183
                               TN  |  -1.134577   .2360435    -4.81   0.000    -1.597214   -.6719403
                               TX  |  -1.246625   .2263804    -5.51   0.000    -1.690323   -.8029278
                               UT  |  -.3710385   .2104719    -1.76   0.078    -.7835559    .0414789
                               VT  |  -.0567346   .2322321    -0.24   0.807    -.5119011     .398432
                               VA  |  -.6988213   .2710867    -2.58   0.010    -1.230141   -.1675011
                               WA  |  -.9910354   .2221787    -4.46   0.000    -1.426498   -.5555731
                               WV  |  -.5011073   .2658406    -1.88   0.059    -1.022145    .0199307
                               WI  |  -.5374685   .2228764    -2.41   0.016    -.9742983   -.1006386
                               WY  |   .1787425   .2109784     0.85   0.397    -.2347675    .5922526
                                   |
                              year |
                             1984  |   .0712534   .0908105     0.78   0.433    -.1067319    .2492387
                             1988  |   .1310588   .0884856     1.48   0.139    -.0423698    .3044875
                             1994  |   .0211461   .0934897     0.23   0.821    -.1620904    .2043825
                             1998  |   -.188592   .1004673    -1.88   0.060    -.3855043    .0083202
                             2004  |  -.2626516   .1055048    -2.49   0.013    -.4694371   -.0558661
                             2008  |  -.2785339   .1215606    -2.29   0.022    -.5167883   -.0402794
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -3.447248   .6593996                     -4.739648   -2.154848
                             /cut2 |  -.3892458   .6503223                     -1.663854    .8853624
                             /cut3 |   .8964217   .6500628                      -.377678    2.170521
                             /cut4 |   2.902703   .6520768                      1.624656     4.18075
----------------------------------------------------------------------------------------------------

. est sto c2

. ologit reve_1c i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r if state!= 11, r 

Iteration 0:   log pseudolikelihood = -10140.076  
Iteration 1:   log pseudolikelihood = -9184.5567  
Iteration 2:   log pseudolikelihood =  -9166.871  
Iteration 3:   log pseudolikelihood =  -9166.828  
Iteration 4:   log pseudolikelihood =  -9166.828  

Ordered logistic regression                     Number of obs     =      7,398
                                                Wald chi2(92)     =    1770.28
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -9166.828               Pseudo R2         =     0.0960

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1c |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.1513383   .0664305    -2.28   0.023    -.2815396    -.021137
                     Man of Color  |  -.5429696   .1025403    -5.30   0.000    -.7439449   -.3419944
                   Woman of Color  |  -.6279113   .1895016    -3.31   0.001    -.9993277   -.2564949
                                   |
                     civil_service |
                              Yes  |  -.4798757    .056244    -8.53   0.000     -.590112   -.3696395
                      weekly_hours |   .0397517   .0029798    13.34   0.000     .0339114    .0455919
                               age |  -.0128594   .0219599    -0.59   0.558    -.0559001    .0301812
                             age_2 |  -.0000152   .0002191    -0.07   0.945    -.0004446    .0004142
                                   |
                               edu |
              High school or less  |   .0337389   .2107636     0.16   0.873    -.3793502     .446828
                     Some college  |  -.1760003   .1085655    -1.62   0.105    -.3887848    .0367842
                   Graduate study  |   .1131381   .0766292     1.48   0.140    -.0370523    .2633286
                  Graduate degree  |   .0478876   .0616145     0.78   0.437    -.0728747    .1686498
                                   |
                years_employ_state |   .0066484   .0039201     1.70   0.090     -.001035    .0143317
               years_employ_agency |  -.0111237   .0041961    -2.65   0.008     -.019348   -.0028994
             years_employ_position |   .0082954   .0054891     1.51   0.131    -.0024631    .0190539
                                   |
                              pid5 |
                       Republican  |   .2378262   .0788692     3.02   0.003     .0832454    .3924069
                  Lean Republican  |  -.0194688   .1004635    -0.19   0.846    -.2163737     .177436
                  Lean Democratic  |   .0045882   .0937989     0.05   0.961    -.1792542    .1884307
                       Democratic  |   .1990113   .0740824     2.69   0.007     .0538124    .3442102
                                   |
                       agency_size |
                           25-100  |   .2707686   .0711666     3.80   0.000     .1312845    .4102526
                          101-500  |   .4889206   .0821769     5.95   0.000     .3278568    .6499844
                        501-1,000  |   .5625396   .1090509     5.16   0.000     .3488037    .7762755
                      1,001-5,000  |   .6404837   .1152733     5.56   0.000     .4145522    .8664152
                       Over 5,000  |   .8958514   .1589755     5.64   0.000     .5842652    1.207438
                                   |
                 log_agency_budget |   .1534062   .0192702     7.96   0.000     .1156373     .191175
                      inst6017_nom |     .00355   .0026366     1.35   0.178    -.0016176    .0087175
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.6961943   .1551997    -4.49   0.000     -1.00038   -.3920085
                Staff: Non-Fiscal  |  -1.350852   .1455773    -9.28   0.000    -1.636178   -1.065526
Income Security & Social Services  |  -1.554606   .1339539   -11.61   0.000    -1.817151   -1.292061
                        Education  |  -1.312727   .1443499    -9.09   0.000    -1.595647   -1.029806
                           Health  |  -1.471954   .1396175   -10.54   0.000    -1.745599   -1.198308
                Natural Resources  |  -.9861432   .1259917    -7.83   0.000    -1.233082   -.7392039
             Environment & Energy  |  -1.179821   .1289078    -9.15   0.000    -1.432475   -.9271659
             Economic Development  |  -1.166863   .1319916    -8.84   0.000    -1.425562   -.9081639
                 Criminal Justice  |  -1.517415   .1332214   -11.39   0.000    -1.778524   -1.256306
                       Regulatory  |  -1.362948   .1248008   -10.92   0.000    -1.607553   -1.118343
                   Transportation  |  -.9424383   .1490835    -6.32   0.000    -1.234637     -.65024
                            Other  |  -1.497146   .1330686   -11.25   0.000    -1.757955   -1.236336
                                   |
                             state |
                               AK  |   .1886826   .2192945     0.86   0.390    -.2411266    .6184919
                               AZ  |   .0691736   .2396533     0.29   0.773    -.4005382    .5388853
                               AR  |   .5983221   .2437515     2.45   0.014     .1205779    1.076066
                               CA  |  -.0982395   .2454834    -0.40   0.689    -.5793782    .3828992
                               CO  |   .3932727   .2119851     1.86   0.064    -.0222106    .8087559
                               CT  |   .1765106   .2436636     0.72   0.469    -.3010612    .6540824
                               DE  |   .1727039   .2282844     0.76   0.449    -.2747254    .6201332
                               FL  |  -.5363477   .2257982    -2.38   0.018    -.9789041   -.0937912
                               GA  |   .3681518   .2271319     1.62   0.105    -.0770186    .8133222
                               ID  |  -.0114861   .2280481    -0.05   0.960    -.4584521      .43548
                               IL  |   .1438285    .249857     0.58   0.565    -.3458823    .6335392
                               IN  |  -.2751811   .2247999    -1.22   0.221    -.7157808    .1654185
                               IA  |  -.0577117   .2162119    -0.27   0.790    -.4814793    .3660558
                               KS  |    .544542   .2182894     2.49   0.013     .1167027    .9723813
                               KY  |  -.5046381   .2364414    -2.13   0.033    -.9680547   -.0412215
                               LA  |    .633825   .2613432     2.43   0.015     .1216018    1.146048
                               ME  |    .858122    .228509     3.76   0.000     .4102526    1.305991
                               MD  |   .2310317   .2193447     1.05   0.292    -.1988761    .6609394
                               MA  |   .4748975   .2547219     1.86   0.062    -.0243483    .9741432
                               MI  |   .8231639    .229052     3.59   0.000     .3742302    1.272098
                               MN  |   .3167935   .2110932     1.50   0.133    -.0969416    .7305287
                               MS  |   .3263103   .2394461     1.36   0.173    -.1429954    .7956161
                               MO  |   .3347998   .2177023     1.54   0.124    -.0918889    .7614884
                               MT  |  -.2884898   .2159547    -1.34   0.182    -.7117532    .1347735
                               NE  |  -.0738096   .2192616    -0.34   0.736    -.5035543    .3559351
                               NV  |  -.7636845   .2112001    -3.62   0.000    -1.177629   -.3497399
                               NH  |   1.070366   .2147012     4.99   0.000     .6495596    1.491173
                               NJ  |  -.4461958   .2418642    -1.84   0.065    -.9202409    .0278493
                               NM  |   -.446875   .2335919    -1.91   0.056    -.9047068    .0109568
                               NY  |  -.5247596    .271367    -1.93   0.053    -1.056629      .00711
                               NC  |  -.1399692   .2020939    -0.69   0.489    -.5360659    .2561275
                               ND  |  -.3956805   .2058704    -1.92   0.055    -.7991791    .0078181
                               OH  |  -.3791564   .2221727    -1.71   0.088    -.8146069    .0562942
                               OK  |   .7637939   .2309359     3.31   0.001     .3111678     1.21642
                               OR  |  -.2805573   .2137788    -1.31   0.189     -.699556    .1384414
                               PA  |   .1052351   .2367162     0.44   0.657    -.3587201    .5691903
                               RI  |  -.0502941   .2455639    -0.20   0.838    -.5315904    .4310022
                               SC  |   1.072214   .2390297     4.49   0.000     .6037243    1.540704
                               SD  |  -.8416119   .2234637    -3.77   0.000    -1.279593   -.4036311
                               TN  |   .0623936   .2395446     0.26   0.795    -.4071052    .5318924
                               TX  |  -.0175185   .2409122    -0.07   0.942    -.4896976    .4546607
                               UT  |  -.5634448   .2118369    -2.66   0.008    -.9786376   -.1482521
                               VT  |   .7497901   .2306896     3.25   0.001     .2976469    1.201933
                               VA  |  -.3181398   .2334944    -1.36   0.173    -.7757804    .1395008
                               WA  |  -.4080592   .2162952    -1.89   0.059      -.83199    .0158716
                               WV  |  -.3717179   .2255863    -1.65   0.099    -.8138589    .0704232
                               WI  |   .2189958   .2075154     1.06   0.291    -.1877268    .6257185
                               WY  |  -.7772091    .218742    -3.55   0.000    -1.205936   -.3484826
                                   |
                              year |
                             1978  |  -.4835081   .0915015    -5.28   0.000    -.6628477   -.3041686
                             1984  |  -.5018126   .0885682    -5.67   0.000     -.675403   -.3282221
                             1988  |  -.4537963   .0833411    -5.45   0.000    -.6171419   -.2904508
                             1994  |   -.469256   .0880376    -5.33   0.000    -.6418066   -.2967054
                             1998  |  -.7093749   .0903177    -7.85   0.000    -.8863944   -.5323555
                             2004  |  -.9707732   .0947819   -10.24   0.000    -1.156542    -.785004
                             2008  |  -.9273312   .1108275    -8.37   0.000    -1.144549   -.7101132
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -4.096121   .6160402                     -5.303537   -2.888704
                             /cut2 |  -.3899673   .6040682                     -1.573919    .7939846
                             /cut3 |   1.100543   .6041442                     -.0835574    2.284644
                             /cut4 |   3.262334   .6051466                      2.076269      4.4484
----------------------------------------------------------------------------------------------------

. est sto c3

. ologit reve_1d i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r if state!= 11 , r 

Iteration 0:   log pseudolikelihood = -8547.4972  
Iteration 1:   log pseudolikelihood = -8026.7826  
Iteration 2:   log pseudolikelihood = -8020.8238  
Iteration 3:   log pseudolikelihood =  -8020.812  
Iteration 4:   log pseudolikelihood =  -8020.812  

Ordered logistic regression                     Number of obs     =      6,211
                                                Wald chi2(91)     =     987.50
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -8020.812               Pseudo R2         =     0.0616

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.0907187   .0689968    -1.31   0.189      -.22595    .0445126
                     Man of Color  |  -.2483621   .1037387    -2.39   0.017    -.4516862   -.0450379
                   Woman of Color  |  -.6379645   .2264187    -2.82   0.005    -1.081737   -.1941921
                                   |
                     civil_service |
                              Yes  |  -.2774085   .0609332    -4.55   0.000    -.3968354   -.1579816
                      weekly_hours |   .0297566   .0031808     9.36   0.000     .0235224    .0359908
                               age |  -.0348477   .0253921    -1.37   0.170    -.0846153      .01492
                             age_2 |   .0002082   .0002537     0.82   0.412     -.000289    .0007053
                                   |
                               edu |
              High school or less  |   .0603826   .2647811     0.23   0.820    -.4585788    .5793441
                     Some college  |   -.071056   .1208704    -0.59   0.557    -.3079576    .1658455
                   Graduate study  |   .1393596   .0829087     1.68   0.093    -.0231384    .3018576
                  Graduate degree  |   .0535909   .0663821     0.81   0.419    -.0765157    .1836975
                                   |
                years_employ_state |   .0139053    .004062     3.42   0.001     .0059439    .0218667
               years_employ_agency |  -.0088735   .0043544    -2.04   0.042    -.0174079   -.0003391
             years_employ_position |   .0045923   .0057125     0.80   0.421     -.006604    .0157887
                                   |
                              pid5 |
                       Republican  |   .0935492   .0833239     1.12   0.262    -.0697626     .256861
                  Lean Republican  |   .0149279   .1108523     0.13   0.893    -.2023387    .2321944
                  Lean Democratic  |   .0117991   .1035899     0.11   0.909    -.1912334    .2148316
                       Democratic  |   .0835414   .0776104     1.08   0.282    -.0685723    .2356551
                                   |
                       agency_size |
                           25-100  |   .0613074   .0752157     0.82   0.415    -.0861127    .2087275
                          101-500  |   .1062628   .0861645     1.23   0.217    -.0626165    .2751422
                        501-1,000  |   .0712378    .119781     0.59   0.552    -.1635287    .3060042
                      1,001-5,000  |   -.023003    .124276    -0.19   0.853    -.2665795    .2205734
                       Over 5,000  |   .2175841   .1695812     1.28   0.199    -.1147888    .5499571
                                   |
                 log_agency_budget |   .1005122   .0210152     4.78   0.000     .0593232    .1417011
                      inst6017_nom |   .0061366   .0029702     2.07   0.039     .0003151    .0119581
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.0600729   .1646003    -0.36   0.715    -.3826835    .2625377
                Staff: Non-Fiscal  |   -.851015   .1665449    -5.11   0.000    -1.177437    -.524593
Income Security & Social Services  |  -.9432952   .1525645    -6.18   0.000    -1.242316   -.6442744
                        Education  |  -.6606785   .1634904    -4.04   0.000    -.9811137   -.3402433
                           Health  |  -.9351175   .1592089    -5.87   0.000    -1.247161   -.6230737
                Natural Resources  |  -.9036672   .1441927    -6.27   0.000     -1.18628   -.6210547
             Environment & Energy  |  -1.043558     .14502    -7.20   0.000    -1.327792   -.7593242
             Economic Development  |  -1.129769   .1492016    -7.57   0.000    -1.422199   -.8373394
                 Criminal Justice  |  -.9675309   .1517799    -6.37   0.000    -1.265014   -.6700477
                       Regulatory  |   -1.16364   .1421071    -8.19   0.000    -1.442165   -.8851154
                   Transportation  |  -.8318832   .1681816    -4.95   0.000    -1.161513   -.5022533
                            Other  |  -.9006386   .1508513    -5.97   0.000    -1.196302   -.6049755
                                   |
                             state |
                               AK  |   1.402699    .254195     5.52   0.000     .9044864    1.900912
                               AZ  |   .9263124   .2657732     3.49   0.000     .4054064    1.447218
                               AR  |   .7171175   .2609152     2.75   0.006      .205733    1.228502
                               CA  |   1.030867    .298289     3.46   0.001     .4462317    1.615503
                               CO  |   .7102792   .2532426     2.80   0.005     .2139329    1.206625
                               CT  |   .5408391   .2846421     1.90   0.057    -.0170493    1.098727
                               DE  |   .0889253    .276412     0.32   0.748    -.4528322    .6306829
                               FL  |   .9121959    .261321     3.49   0.000     .4000162    1.424376
                               GA  |   .4892834   .2739221     1.79   0.074     -.047594    1.026161
                               ID  |   .5399738   .2541959     2.12   0.034     .0417591    1.038189
                               IL  |   .5315369    .286029     1.86   0.063    -.0290696    1.092143
                               IN  |   .1959949   .2680057     0.73   0.465    -.3292867    .7212764
                               IA  |   .4571054   .2520675     1.81   0.070    -.0369378    .9511487
                               KS  |   1.195698   .2590969     4.61   0.000     .6878774    1.703519
                               KY  |   .6166384    .262767     2.35   0.019     .1016245    1.131652
                               LA  |   .8073772    .290327     2.78   0.005     .2383467    1.376408
                               ME  |   .8888268   .2866087     3.10   0.002      .327084     1.45057
                               MD  |   .7965676   .2597702     3.07   0.002     .2874274    1.305708
                               MA  |   .8795089   .2936773     2.99   0.003      .303912    1.455106
                               MI  |   1.698361   .2704831     6.28   0.000     1.168224    2.228498
                               MN  |   1.182742   .2509347     4.71   0.000     .6909185    1.674565
                               MS  |   .4345177   .2623061     1.66   0.098    -.0795928    .9486283
                               MO  |   .7493641   .2607095     2.87   0.004     .2383829    1.260345
                               MT  |   .3977648   .2476948     1.61   0.108    -.0877081    .8832377
                               NE  |   .9321928    .259348     3.59   0.000       .42388    1.440506
                               NV  |    .416083   .2480752     1.68   0.093    -.0701354    .9023015
                               NH  |   .8647275   .2776311     3.11   0.002     .3205806    1.408874
                               NJ  |   .3146922   .2665383     1.18   0.238    -.2077132    .8370977
                               NM  |   .4515524    .271609     1.66   0.096    -.0807914    .9838962
                               NY  |   .3914384    .354313     1.10   0.269    -.3030022    1.085879
                               NC  |   .3001386   .2430446     1.23   0.217    -.1762201    .7764973
                               ND  |  -.6441832   .2581331    -2.50   0.013    -1.150115   -.1382516
                               OH  |   .5210619   .2835115     1.84   0.066    -.0346103    1.076734
                               OK  |   1.094113   .2578313     4.24   0.000     .5887726    1.599453
                               OR  |   .6206606   .2585935     2.40   0.016     .1138267    1.127495
                               PA  |   1.028203   .2769874     3.71   0.000     .4853179    1.571089
                               RI  |  -.2573367   .2872883    -0.90   0.370    -.8204114    .3057379
                               SC  |   1.396252   .2786003     5.01   0.000     .8502056    1.942299
                               SD  |  -.2985064   .2595108    -1.15   0.250    -.8071383    .2101255
                               TN  |   .5319439   .2692353     1.98   0.048     .0042524    1.059635
                               TX  |   1.562835   .2666988     5.86   0.000     1.040115    2.085555
                               UT  |   .5451191   .2410795     2.26   0.024     .0726119    1.017626
                               VT  |   .2805212   .2776293     1.01   0.312    -.2636223    .8246647
                               VA  |   .3091471   .2627947     1.18   0.239    -.2059211    .8242154
                               WA  |   .6125016   .2411716     2.54   0.011      .139814    1.085189
                               WV  |   .1113054   .2617384     0.43   0.671    -.4016925    .6243033
                               WI  |   1.246155   .2566164     4.86   0.000     .7431961    1.749114
                               WY  |  -.3048764   .2545339    -1.20   0.231    -.8037537     .194001
                                   |
                              year |
                             1984  |  -.1175692   .0909797    -1.29   0.196    -.2958861    .0607478
                             1988  |   .1440234   .0877922     1.64   0.101    -.0280462     .316093
                             1994  |   .1878769   .0933425     2.01   0.044     .0049289    .3708249
                             1998  |  -.0817928   .0991821    -0.82   0.410    -.2761862    .1126005
                             2004  |  -.4470666    .101541    -4.40   0.000    -.6460833     -.24805
                             2008  |  -.2206094   .1147801    -1.92   0.055    -.4455743    .0043556
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -3.098221   .6983528                     -4.466967   -1.729474
                             /cut2 |  -.0410445   .6916011                     -1.396558    1.314469
                             /cut3 |   1.393458   .6918058                      .0375439    2.749373
                             /cut4 |   3.563286   .6930047                      2.205022     4.92155
----------------------------------------------------------------------------------------------------

. est sto c4

. ologit d_15a i.intersection i.reve_1a i.reve_1b i.civil_service weekly_hours age age_2 b3.edu years_employ_
> state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fun
> cat13 i.state i.year if state!= 11 , r 

Iteration 0:   log pseudolikelihood = -6307.5233  
Iteration 1:   log pseudolikelihood = -5706.1535  
Iteration 2:   log pseudolikelihood = -5676.7638  
Iteration 3:   log pseudolikelihood = -5676.5069  
Iteration 4:   log pseudolikelihood = -5676.5067  

Ordered logistic regression                     Number of obs     =      6,099
                                                Wald chi2(99)     =    1101.22
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -5676.5067               Pseudo R2         =     0.1000

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_15a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.1179364   .0787753    -1.50   0.134    -.2723332    .0364604
                     Man of Color  |   .3157412   .1239966     2.55   0.011     .0727124      .55877
                   Woman of Color  |   .6015427   .2557873     2.35   0.019     .1002088    1.102877
                                   |
                           reve_1a |
                Less than Monthly  |   .2263048   .0815758     2.77   0.006     .0664191    .3861904
                          Monthly  |   .2499633   .1052035     2.38   0.018     .0437683    .4561583
                           Weekly  |   .5541822   .1383913     4.00   0.000     .2829404    .8254241
                            Daily  |   1.448185   .3666939     3.95   0.000     .7294785    2.166892
                                   |
                           reve_1b |
                Less than Monthly  |   .4595109   .2009953     2.29   0.022     .0655675    .8534544
                          Monthly  |   .6935854   .2060167     3.37   0.001        .2898    1.097371
                           Weekly  |   1.144004   .2111329     5.42   0.000     .7301909    1.557817
                            Daily  |   1.670692   .2302298     7.26   0.000      1.21945    2.121934
                                   |
                     civil_service |
                              Yes  |   .1481754   .0698925     2.12   0.034     .0111886    .2851623
                      weekly_hours |  -.0058141    .003653    -1.59   0.111    -.0129739    .0013457
                               age |   .0158009   .0256494     0.62   0.538     -.034471    .0660729
                             age_2 |  -.0002359   .0002536    -0.93   0.352     -.000733    .0002611
                                   |
                               edu |
              High school or less  |  -.0095348   .2635123    -0.04   0.971    -.5260095    .5069399
                     Some college  |  -.2450478   .1364042    -1.80   0.072     -.512395    .0222995
                   Graduate study  |   .1417724   .0973337     1.46   0.145    -.0489982    .3325429
                  Graduate degree  |  -.1229886   .0768924    -1.60   0.110     -.273695    .0277177
                                   |
                years_employ_state |  -.0005542   .0048237    -0.11   0.909    -.0100084       .0089
               years_employ_agency |  -.0030854   .0050763    -0.61   0.543    -.0130349     .006864
             years_employ_position |  -.0200206   .0064481    -3.10   0.002    -.0326586   -.0073827
                                   |
                              pid5 |
                       Republican  |  -.0149773   .0941387    -0.16   0.874    -.1994859    .1695312
                  Lean Republican  |  -.0459736   .1205626    -0.38   0.703     -.282272    .1903248
                  Lean Democratic  |  -.0902175   .1120406    -0.81   0.421    -.3098131    .1293781
                       Democratic  |  -.0835085   .0870062    -0.96   0.337    -.2540376    .0870206
                                   |
                       agency_size |
                           25-100  |   .0520769   .0873591     0.60   0.551    -.1191438    .2232977
                          101-500  |  -.1131532   .0987776    -1.15   0.252    -.3067538    .0804475
                        501-1,000  |  -.1006597   .1291857    -0.78   0.436     -.353859    .1525395
                      1,001-5,000  |  -.2061329   .1366756    -1.51   0.132    -.4740121    .0617463
                       Over 5,000  |  -.1551127   .1888923    -0.82   0.412    -.5253347    .2151093
                                   |
                 log_agency_budget |   .0455632   .0229946     1.98   0.048     .0004945    .0906318
                      inst6017_nom |  -.0017474   .0033669    -0.52   0.604    -.0083464    .0048517
                                   |
                          funcat13 |
                    Staff: Fiscal  |   2.537026   .1875692    13.53   0.000     2.169398    2.904655
                Staff: Non-Fiscal  |   2.869192   .1871047    15.33   0.000     2.502473     3.23591
Income Security & Social Services  |   1.954471   .1557797    12.55   0.000     1.649148    2.259794
                        Education  |   1.771533   .1665307    10.64   0.000     1.445139    2.097927
                           Health  |   1.936811   .1628186    11.90   0.000     1.617692     2.25593
                Natural Resources  |   1.847427   .1446244    12.77   0.000     1.563969    2.130886
             Environment & Energy  |   2.488539   .1565195    15.90   0.000     2.181766    2.795311
             Economic Development  |   2.201224   .1648795    13.35   0.000     1.878066    2.524382
                 Criminal Justice  |   2.211654   .1575861    14.03   0.000     1.902791    2.520517
                       Regulatory  |   1.803483   .1472059    12.25   0.000     1.514965    2.092002
                   Transportation  |    2.33935    .178484    13.11   0.000     1.989527    2.689172
                            Other  |   1.890402   .1581267    11.95   0.000     1.580479    2.200325
                                   |
                             state |
                               AK  |   1.117765   .2506546     4.46   0.000     .6264908    1.609039
                               AZ  |   .4979669   .2734527     1.82   0.069    -.0379905    1.033924
                               AR  |   .9459118    .283273     3.34   0.001     .3907068    1.501117
                               CA  |   1.432033   .3057058     4.68   0.000     .8328604    2.031205
                               CO  |   .2400067   .2482541     0.97   0.334    -.2465623    .7265757
                               CT  |   1.163278   .3236079     3.59   0.000     .5290185    1.797538
                               DE  |   1.283001   .2521186     5.09   0.000     .7888571    1.777144
                               FL  |   .7603088   .2767324     2.75   0.006     .2179233    1.302694
                               GA  |   .9717328   .2599781     3.74   0.000     .4621852    1.481281
                               ID  |    .534177   .2517658     2.12   0.034      .040725    1.027629
                               IL  |   1.137131   .3118301     3.65   0.000     .5259548    1.748306
                               IN  |    1.02322   .2698661     3.79   0.000     .4942921    1.552148
                               IA  |   .7488865    .253976     2.95   0.003     .2511026     1.24667
                               KS  |   1.124702   .2756223     4.08   0.000     .5844922    1.664912
                               KY  |    1.12773   .2699555     4.18   0.000     .5986273    1.656834
                               LA  |   .7580872    .300052     2.53   0.012      .169996    1.346178
                               ME  |   1.070142   .2791016     3.83   0.000     .5231125    1.617171
                               MD  |   1.278272   .2644787     4.83   0.000     .7599027     1.79664
                               MA  |   .7196831   .2735155     2.63   0.009     .1836026    1.255764
                               MI  |   1.243199   .2543934     4.89   0.000     .7445972    1.741801
                               MN  |   .9019909   .2369163     3.81   0.000     .4376435    1.366338
                               MS  |  -.3769148   .2527041    -1.49   0.136    -.8722057    .1183761
                               MO  |   .8454676   .2561733     3.30   0.001     .3433771    1.347558
                               MT  |   .6157092   .2448752     2.51   0.012     .1357628    1.095656
                               NE  |   .8802851   .2525267     3.49   0.000     .3853419    1.375228
                               NV  |   1.011986   .2624677     3.86   0.000     .4975591    1.526414
                               NH  |   .9792745   .2759473     3.55   0.000     .4384279    1.520121
                               NJ  |   1.616407   .2864854     5.64   0.000     1.054906    2.177909
                               NM  |   1.091984   .2774161     3.94   0.000     .5482582    1.635709
                               NY  |   1.688779   .3995275     4.23   0.000     .9057197    2.471839
                               NC  |   .7386991     .23404     3.16   0.002     .2799892    1.197409
                               ND  |   .5755144   .2399423     2.40   0.016     .1052361    1.045793
                               OH  |   .9092219   .2666856     3.41   0.001     .3865278    1.431916
                               OK  |   .2561369   .2441171     1.05   0.294    -.2223237    .7345975
                               OR  |   .6064145   .2457387     2.47   0.014     .1247755    1.088054
                               PA  |   1.199324   .2586824     4.64   0.000     .6923159    1.706332
                               RI  |   .9910618   .2914373     3.40   0.001     .4198552    1.562268
                               SC  |  -.0801767   .2569707    -0.31   0.755    -.5838299    .4234765
                               SD  |   1.068992   .2671592     4.00   0.000     .5453695    1.592614
                               TN  |   .9722365   .2592522     3.75   0.000     .4641115    1.480362
                               TX  |  -.3723179    .254603    -1.46   0.144    -.8713307    .1266949
                               UT  |   .9583438   .2363705     4.05   0.000     .4950661    1.421621
                               VT  |   1.094328   .2755318     3.97   0.000     .5542957    1.634361
                               VA  |    1.16876   .2804659     4.17   0.000     .6190575    1.718463
                               WA  |   .8640006   .2685014     3.22   0.001     .3377476    1.390254
                               WV  |   .5595551   .2682297     2.09   0.037     .0338345    1.085276
                               WI  |   1.577202   .2629178     6.00   0.000     1.061892    2.092511
                               WY  |   .5382086    .246644     2.18   0.029     .0547952    1.021622
                                   |
                              year |
                             1984  |   .1685453   .1025435     1.64   0.100    -.0324363    .3695268
                             1988  |   .1076082   .0974224     1.10   0.269    -.0833362    .2985525
                             1994  |   .4491783   .1054548     4.26   0.000     .2424908    .6558659
                             1998  |   .6414729   .1135988     5.65   0.000     .4188234    .8641225
                             2004  |   .2867526   .1153674     2.49   0.013     .0606366    .5128686
                             2008  |    .557964   .1253455     4.45   0.000     .3122913    .8036367
-----------------------------------+----------------------------------------------------------------
                             /cut1 |   .0706139   .7225094                     -1.345479    1.486706
                             /cut2 |   2.055948   .7250258                      .6349235    3.476972
                             /cut3 |   3.651473    .726562                      2.227437    5.075508
----------------------------------------------------------------------------------------------------

. est sto c5

. ologit d_16a i.intersection i.reve_1c  i.reve_1d i.civil_service weekly_hours age age_2 b3.edu years_employ
> _state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fu
> ncat13 i.state i.year if state!= 11 , r 

Iteration 0:   log pseudolikelihood = -6510.8532  
Iteration 1:   log pseudolikelihood = -6291.4795  
Iteration 2:   log pseudolikelihood =  -6290.242  
Iteration 3:   log pseudolikelihood = -6290.2415  

Ordered logistic regression                     Number of obs     =      6,076
                                                Wald chi2(99)     =     420.45
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -6290.2415               Pseudo R2         =     0.0339

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_16a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |   .0541218   .0727911     0.74   0.457    -.0885463    .1967898
                     Man of Color  |   .2989393   .1171377     2.55   0.011     .0693535     .528525
                   Woman of Color  |   .4506498   .2246132     2.01   0.045      .010416    .8908835
                                   |
                           reve_1c |
                Less than Monthly  |  -.4471674     .28977    -1.54   0.123    -1.015106    .1207715
                          Monthly  |  -.3677423   .2917088    -1.26   0.207     -.939481    .2039963
                           Weekly  |  -.2317974   .2953799    -0.78   0.433    -.8107314    .3471366
                            Daily  |  -.2862969   .3144275    -0.91   0.363    -.9025635    .3299696
                                   |
                           reve_1d |
                Less than Monthly  |   .5252773   .2158458     2.43   0.015     .1022273    .9483274
                          Monthly  |   .6986243   .2154209     3.24   0.001     .2764071    1.120842
                           Weekly  |   .8725149   .2181059     4.00   0.000     .4450351    1.299995
                            Daily  |   1.253253   .2443735     5.13   0.000     .7742895    1.732216
                                   |
                     civil_service |
                              Yes  |   .0881555   .0654098     1.35   0.178    -.0400453    .2163564
                      weekly_hours |  -.0025265   .0032892    -0.77   0.442    -.0089731    .0039202
                               age |   .0489934   .0236717     2.07   0.038     .0025978     .095389
                             age_2 |  -.0004469   .0002352    -1.90   0.057    -.0009078     .000014
                                   |
                               edu |
              High school or less  |   .0357543   .2787451     0.13   0.898    -.5105761    .5820847
                     Some college  |  -.1317618   .1256043    -1.05   0.294    -.3779417    .1144182
                   Graduate study  |   .0494111   .0880152     0.56   0.575    -.1230956    .2219178
                  Graduate degree  |  -.0748315   .0719756    -1.04   0.298     -.215901     .066238
                                   |
                years_employ_state |   .0079519   .0044944     1.77   0.077    -.0008569    .0167608
               years_employ_agency |  -.0093529   .0047163    -1.98   0.047    -.0185967   -.0001091
             years_employ_position |   -.008571   .0062928    -1.36   0.173    -.0209047    .0037626
                                   |
                              pid5 |
                       Republican  |  -.1518195   .0876705    -1.73   0.083    -.3236505    .0200114
                  Lean Republican  |   .0408477   .1141297     0.36   0.720    -.1828425    .2645378
                  Lean Democratic  |    .019786   .1091432     0.18   0.856    -.1941307    .2337028
                       Democratic  |  -.0922908   .0831154    -1.11   0.267     -.255194    .0706124
                                   |
                       agency_size |
                           25-100  |   .1245927    .082154     1.52   0.129    -.0364262    .2856117
                          101-500  |   .1327067    .094173     1.41   0.159    -.0518689    .3172823
                        501-1,000  |  -.0140369   .1227774    -0.11   0.909    -.2546763    .2266024
                      1,001-5,000  |   -.144105   .1296676    -1.11   0.266    -.3982489    .1100388
                       Over 5,000  |   -.111164   .1773575    -0.63   0.531    -.4587782    .2364503
                                   |
                 log_agency_budget |   .0332697   .0215951     1.54   0.123     -.009056    .0755954
                      inst6017_nom |   .0088423   .0031956     2.77   0.006      .002579    .0151055
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.0960019   .1720379    -0.56   0.577    -.4331899    .2411862
                Staff: Non-Fiscal  |   .0128244    .175448     0.07   0.942    -.3310473    .3566961
Income Security & Social Services  |  -.2123409   .1627019    -1.31   0.192    -.5312307     .106549
                        Education  |   .1088222   .1837058     0.59   0.554    -.2512346    .4688791
                           Health  |   .0410027   .1740128     0.24   0.814    -.3000561    .3820615
                Natural Resources  |  -.2596275   .1531443    -1.70   0.090    -.5597848    .0405298
             Environment & Energy  |   .1197552   .1614634     0.74   0.458    -.1967073    .4362176
             Economic Development  |  -.3371728   .1632645    -2.07   0.039    -.6571654   -.0171802
                 Criminal Justice  |   .1941964   .1657979     1.17   0.241    -.1307616    .5191544
                       Regulatory  |    .037814   .1553255     0.24   0.808    -.2666183    .3422463
                   Transportation  |   .1015581   .1732667     0.59   0.558    -.2380385    .4411547
                            Other  |  -.4663834   .1625308    -2.87   0.004     -.784938   -.1478289
                                   |
                             state |
                               AK  |   .7733893   .2435025     3.18   0.001     .2961331    1.250645
                               AZ  |    .840547   .2608227     3.22   0.001      .329344     1.35175
                               AR  |   .6231876   .2493553     2.50   0.012     .1344601    1.111915
                               CA  |   .8307298    .271569     3.06   0.002     .2984643    1.362995
                               CO  |   1.020228   .2546331     4.01   0.000     .5211562      1.5193
                               CT  |   .8329517   .2919019     2.85   0.004     .2608346    1.405069
                               DE  |   .9292616   .2494032     3.73   0.000     .4404402    1.418083
                               FL  |   1.179669   .2616749     4.51   0.000     .6667954    1.692542
                               GA  |   .5084011   .2701283     1.88   0.060    -.0210407    1.037843
                               ID  |   .7777533   .2498611     3.11   0.002     .2880346    1.267472
                               IL  |   .4199304   .2700828     1.55   0.120    -.1094221     .949283
                               IN  |   .5971314   .2442899     2.44   0.015     .1183319    1.075931
                               IA  |    .954611   .2414233     3.95   0.000     .4814299    1.427792
                               KS  |   1.252132   .2584332     4.85   0.000     .7456119    1.758652
                               KY  |   .5370993   .2457023     2.19   0.029     .0555316    1.018667
                               LA  |   .1523949   .2648664     0.58   0.565    -.3667337    .6715236
                               ME  |   1.154491   .2731684     4.23   0.000     .6190908    1.689891
                               MD  |   .4821681   .2544056     1.90   0.058    -.0164578    .9807939
                               MA  |   -.035309   .2571799    -0.14   0.891    -.5393724    .4687544
                               MI  |   .1517865   .2474228     0.61   0.540    -.3331533    .6367263
                               MN  |   1.194292   .2433795     4.91   0.000     .7172769    1.671307
                               MS  |   .9468364    .256262     3.69   0.000     .4445722    1.449101
                               MO  |   .4507284   .2467465     1.83   0.068    -.0328858    .9343427
                               MT  |   .7479287   .2325699     3.22   0.001     .2921001    1.203757
                               NE  |     1.0412   .2549436     4.08   0.000       .54152    1.540881
                               NV  |   1.012099   .2470723     4.10   0.000     .5278458    1.496352
                               NH  |   1.340658   .2606135     5.14   0.000     .8298653    1.851451
                               NJ  |    .763581    .259741     2.94   0.003     .2544979    1.272664
                               NM  |   .7251755   .2630699     2.76   0.006     .2095679    1.240783
                               NY  |   .5877822   .2848262     2.06   0.039     .0295331    1.146031
                               NC  |   .8348283   .2366415     3.53   0.000     .3710195    1.298637
                               ND  |   .8705289   .2407767     3.62   0.000     .3986151    1.342443
                               OH  |   .4335211   .2518229     1.72   0.085    -.0600426    .9270849
                               OK  |   1.265845   .2569325     4.93   0.000     .7622662    1.769423
                               OR  |   1.352393     .25084     5.39   0.000     .8607558    1.844031
                               PA  |   .0834947   .2459321     0.34   0.734    -.3985234    .5655128
                               RI  |   .4171907   .2711512     1.54   0.124    -.1142559    .9486374
                               SC  |   .8024723    .272586     2.94   0.003     .2682135    1.336731
                               SD  |   .4905802   .2428214     2.02   0.043      .014659    .9665014
                               TN  |   .2072382   .2544915     0.81   0.415     -.291556    .7060323
                               TX  |   1.292727   .2743623     4.71   0.000     .7549869    1.830468
                               UT  |   1.170004   .2466666     4.74   0.000     .6865458    1.653461
                               VT  |      .7182   .2470587     2.91   0.004     .2339737    1.202426
                               VA  |   1.008696   .2671832     3.78   0.000     .4850267    1.532365
                               WA  |   .8346272   .2609571     3.20   0.001     .3231606    1.346094
                               WV  |   .6043127   .2598519     2.33   0.020     .0950124    1.113613
                               WI  |   .7367455   .2447498     3.01   0.003     .2570447    1.216446
                               WY  |   .7925578   .2496255     3.17   0.001     .3033008    1.281815
                                   |
                              year |
                             1984  |   .0327488   .0941481     0.35   0.728     -.151778    .2172757
                             1988  |   .0105805   .0892431     0.12   0.906    -.1643329    .1854938
                             1994  |   .1729326    .097374     1.78   0.076     -.017917    .3637822
                             1998  |   .3508021   .1031066     3.40   0.001      .148717    .5528873
                             2004  |   .0610036   .1077582     0.57   0.571    -.1501985    .2722057
                             2008  |   .2186856   .1170311     1.87   0.062    -.0106912    .4480623
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.152417   .7422845                     -2.607267    .3024342
                             /cut2 |   1.121263   .7375217                     -.3242527    2.566779
                             /cut3 |   2.992481   .7384134                      1.545218    4.439745
----------------------------------------------------------------------------------------------------

. est sto c6

. ologit d_20a i.intersection i.reve_1a i.reve_1b  i.civil_service weekly_hours age age_2 b3.edu years_employ
> _state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fu
> ncat13 i.state i.year if state!= 11 , r  

Iteration 0:   log pseudolikelihood = -7839.3713  
Iteration 1:   log pseudolikelihood = -7357.6758  
Iteration 2:   log pseudolikelihood = -7351.9293  
Iteration 3:   log pseudolikelihood = -7351.9184  
Iteration 4:   log pseudolikelihood = -7351.9184  

Ordered logistic regression                     Number of obs     =      6,051
                                                Wald chi2(99)     =     897.99
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -7351.9184               Pseudo R2         =     0.0622

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_20a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.2189762   .0697562    -3.14   0.002    -.3556958   -.0822565
                     Man of Color  |   .1971906   .1086272     1.82   0.069    -.0157147     .410096
                   Woman of Color  |   .4198783   .2060734     2.04   0.042     .0159818    .8237748
                                   |
                           reve_1a |
                Less than Monthly  |    .215235   .0789759     2.73   0.006     .0604451    .3700249
                          Monthly  |   .2658895   .0995917     2.67   0.008     .0706933    .4610856
                           Weekly  |   .3908623   .1200495     3.26   0.001     .1555696     .626155
                            Daily  |   .6139118   .2210855     2.78   0.005     .1805921    1.047231
                                   |
                           reve_1b |
                Less than Monthly  |   .3607557   .2061338     1.75   0.080    -.0432591    .7647705
                          Monthly  |   .5551027   .2109158     2.63   0.008     .1417153    .9684901
                           Weekly  |   .7795744   .2135893     3.65   0.000     .3609471    1.198202
                            Daily  |   1.016324    .224977     4.52   0.000     .5753773    1.457271
                                   |
                     civil_service |
                              Yes  |   .2155313   .0649833     3.32   0.001     .0881663    .3428962
                      weekly_hours |  -.0012521   .0032457    -0.39   0.700    -.0076136    .0051093
                               age |  -.0259699   .0235526    -1.10   0.270     -.072132    .0201923
                             age_2 |   .0002102   .0002332     0.90   0.367    -.0002468    .0006672
                                   |
                               edu |
              High school or less  |   .3339774   .2638407     1.27   0.206     -.183141    .8510957
                     Some college  |   -.084247   .1277433    -0.66   0.510    -.3346193    .1661253
                   Graduate study  |  -.0458143   .0847953    -0.54   0.589    -.2120101    .1203815
                  Graduate degree  |   -.264484   .0698899    -3.78   0.000    -.4014658   -.1275023
                                   |
                years_employ_state |   .0017314   .0042894     0.40   0.686    -.0066757    .0101385
               years_employ_agency |  -.0015786   .0045491    -0.35   0.729    -.0104947    .0073376
             years_employ_position |  -.0257305    .006324    -4.07   0.000    -.0381254   -.0133357
                                   |
                              pid5 |
                       Republican  |    .122968   .0875723     1.40   0.160    -.0486706    .2946066
                  Lean Republican  |   .0676789   .1104083     0.61   0.540    -.1487174    .2840752
                  Lean Democratic  |   .0634319   .1009628     0.63   0.530    -.1344515    .2613154
                       Democratic  |   .0595968   .0807864     0.74   0.461    -.0987416    .2179352
                                   |
                       agency_size |
                           25-100  |  -.1184071   .0816133    -1.45   0.147    -.2783661     .041552
                          101-500  |  -.2757451   .0898052    -3.07   0.002    -.4517602   -.0997301
                        501-1,000  |  -.3957908   .1157667    -3.42   0.001    -.6226893   -.1688923
                      1,001-5,000  |  -.4505337   .1209086    -3.73   0.000    -.6875103   -.2135572
                       Over 5,000  |  -.5072316   .1623746    -3.12   0.002    -.8254801   -.1889831
                                   |
                 log_agency_budget |   .0069784   .0197367     0.35   0.724    -.0317049    .0456616
                      inst6017_nom |   -.003862   .0029763    -1.30   0.194    -.0096954    .0019713
                                   |
                          funcat13 |
                    Staff: Fiscal  |   2.133404   .1829306    11.66   0.000     1.774866    2.491941
                Staff: Non-Fiscal  |    2.49113   .1832184    13.60   0.000     2.132028    2.850231
Income Security & Social Services  |   1.844827   .1701064    10.85   0.000     1.511424    2.178229
                        Education  |    1.45764   .1793514     8.13   0.000     1.106118    1.809162
                           Health  |   1.873708   .1786879    10.49   0.000     1.523486     2.22393
                Natural Resources  |   1.659724   .1612968    10.29   0.000     1.343588     1.97586
             Environment & Energy  |   1.744091   .1670257    10.44   0.000     1.416726    2.071455
             Economic Development  |   1.733787   .1728394    10.03   0.000     1.395028    2.072546
                 Criminal Justice  |   1.748551   .1711961    10.21   0.000     1.413013     2.08409
                       Regulatory  |   1.208197   .1626039     7.43   0.000      .889499    1.526895
                   Transportation  |    1.82858   .1805322    10.13   0.000     1.474743    2.182416
                            Other  |   1.796552   .1751114    10.26   0.000     1.453341    2.139764
                                   |
                             state |
                               AK  |   1.088559    .250621     4.34   0.000     .5973507    1.579767
                               AZ  |   .5336882   .2681321     1.99   0.047     .0081589    1.059217
                               AR  |   .7690733   .2596478     2.96   0.003     .2601728    1.277974
                               CA  |   1.177171   .2987926     3.94   0.000      .591548    1.762793
                               CO  |  -.4957462   .2460126    -2.02   0.044     -.977922   -.0135704
                               CT  |   .3989674   .3054613     1.31   0.192    -.1997258    .9976606
                               DE  |    .486304    .240045     2.03   0.043     .0158243    .9567836
                               FL  |   .6031937   .2570289     2.35   0.019     .0994264    1.106961
                               GA  |   .5637795   .2453916     2.30   0.022     .0828208    1.044738
                               ID  |   .2415705   .2478343     0.97   0.330    -.2441758    .7273167
                               IL  |   .7036999   .2837864     2.48   0.013     .1474888    1.259911
                               IN  |   1.338305   .2516845     5.32   0.000     .8450129    1.831598
                               IA  |   .5581819   .2291419     2.44   0.015      .109072    1.007292
                               KS  |    .489581   .2638826     1.86   0.064    -.0276195    1.006781
                               KY  |   1.265364   .2645177     4.78   0.000     .7469189    1.783809
                               LA  |   .6139208   .2638543     2.33   0.020     .0967759    1.131066
                               ME  |   .0476684   .2558908     0.19   0.852    -.4538683    .5492051
                               MD  |   .6098569   .2593435     2.35   0.019      .101553    1.118161
                               MA  |   .8954531    .283066     3.16   0.002      .340654    1.450252
                               MI  |   .9824859    .248425     3.95   0.000     .4955818     1.46939
                               MN  |  -.0037399   .2336507    -0.02   0.987    -.4616868    .4542069
                               MS  |  -.3365509   .2710089    -1.24   0.214    -.8677185    .1946168
                               MO  |   .3863249   .2398193     1.61   0.107    -.0837123     .856362
                               MT  |   .1856862   .2406478     0.77   0.440    -.2859747    .6573472
                               NE  |   .8083417   .2421467     3.34   0.001      .333743     1.28294
                               NV  |   .5659884   .2440153     2.32   0.020     .0877272     1.04425
                               NH  |   .0658152    .255822     0.26   0.797    -.4355867    .5672171
                               NJ  |   1.259053   .2695065     4.67   0.000     .7308299    1.787276
                               NM  |     .41014   .2612709     1.57   0.116    -.1019415    .9222216
                               NY  |   1.210699   .2943196     4.11   0.000     .6338436    1.787555
                               NC  |   .5129268   .2307292     2.22   0.026     .0607058    .9651477
                               ND  |   .2130358   .2449211     0.87   0.384    -.2670007    .6930723
                               OH  |   .6330884   .2371692     2.67   0.008     .1682453    1.097931
                               OK  |   .7173418   .2539387     2.82   0.005     .2196312    1.215052
                               OR  |    .230751   .2341661     0.99   0.324    -.2282062    .6897081
                               PA  |   1.325695   .2500167     5.30   0.000      .835671    1.815718
                               RI  |    .565595   .2633793     2.15   0.032      .049381    1.081809
                               SC  |   .0484748   .2461189     0.20   0.844    -.4339094     .530859
                               SD  |    .585284   .2465619     2.37   0.018     .1020315    1.068537
                               TN  |   .9700536   .2639842     3.67   0.000      .452654    1.487453
                               TX  |  -.1094511   .2557893    -0.43   0.669    -.6107888    .3918866
                               UT  |   .6465589   .2320741     2.79   0.005      .191702    1.101416
                               VT  |   .6880359   .2506255     2.75   0.006     .1968189    1.179253
                               VA  |   1.273214   .2739101     4.65   0.000     .7363604    1.810068
                               WA  |   .3285523   .2493376     1.32   0.188    -.1601404     .817245
                               WV  |   .4806239   .2490593     1.93   0.054    -.0075234    .9687713
                               WI  |   .7246256   .2336178     3.10   0.002     .2667431    1.182508
                               WY  |   .8311132   .2539317     3.27   0.001     .3334163     1.32881
                                   |
                              year |
                             1984  |  -.0506342   .0981365    -0.52   0.606    -.2429782    .1417098
                             1988  |  -.1910317     .09364    -2.04   0.041    -.3745627   -.0075007
                             1994  |   .2768582    .099043     2.80   0.005     .0827375    .4709789
                             1998  |   .4257755   .1032502     4.12   0.000     .2234089    .6281421
                             2004  |  -.0719913   .1065175    -0.68   0.499    -.2807617    .1367791
                             2008  |   .3029944   .1116567     2.71   0.007     .0841514    .5218374
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -.8370286   .6594787                     -2.129583     .455526
                             /cut2 |   1.341742   .6595268                       .049093     2.63439
                             /cut3 |   2.828958   .6602201                       1.53495    4.122965
----------------------------------------------------------------------------------------------------

. est sto c7

. ologit d_21a i.intersection i.reve_1c i.reve_1d i.civil_service weekly_hours age age_2 b3.edu years_employ_
> state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fun
> cat13 i.state i.year if state!= 11 , r 

Iteration 0:   log pseudolikelihood =  -7530.654  
Iteration 1:   log pseudolikelihood =  -7313.901  
Iteration 2:   log pseudolikelihood = -7312.8768  
Iteration 3:   log pseudolikelihood = -7312.8764  

Ordered logistic regression                     Number of obs     =      6,034
                                                Wald chi2(99)     =     418.03
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -7312.8764               Pseudo R2         =     0.0289

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_21a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.0704301   .0690859    -1.02   0.308     -.205836    .0649759
                     Man of Color  |   .3770545   .1011982     3.73   0.000     .1787097    .5753993
                   Woman of Color  |   .5676001   .2140552     2.65   0.008     .1480597    .9871405
                                   |
                           reve_1c |
                Less than Monthly  |   .1326859   .2899063     0.46   0.647    -.4355201    .7008918
                          Monthly  |    .084714   .2911775     0.29   0.771    -.4859834    .6554114
                           Weekly  |   .1459307   .2948664     0.49   0.621    -.4319968    .7238582
                            Daily  |   .0970304   .3087393     0.31   0.753    -.5080875    .7021483
                                   |
                           reve_1d |
                Less than Monthly  |   .6942681   .2165668     3.21   0.001      .269805    1.118731
                          Monthly  |   .8597798   .2169796     3.96   0.000     .4345076    1.285052
                           Weekly  |   .9466419   .2205323     4.29   0.000     .5144065    1.378877
                            Daily  |   1.168718   .2388213     4.89   0.000     .7006368    1.636799
                                   |
                     civil_service |
                              Yes  |   .0890151   .0637523     1.40   0.163    -.0359371    .2139672
                      weekly_hours |   .0006808   .0031983     0.21   0.831    -.0055877    .0069493
                               age |  -.0283315   .0250917    -1.13   0.259    -.0775104    .0208474
                             age_2 |   .0003194   .0002503     1.28   0.202    -.0001711      .00081
                                   |
                               edu |
              High school or less  |   .3177241   .2802188     1.13   0.257    -.2314947    .8669429
                     Some college  |  -.2365698   .1277837    -1.85   0.064    -.4870212    .0138817
                   Graduate study  |  -.1101491   .0860955    -1.28   0.201    -.2788933    .0585951
                  Graduate degree  |  -.2471027   .0688044    -3.59   0.000    -.3819568   -.1122487
                                   |
                years_employ_state |  -.0036826   .0040829    -0.90   0.367    -.0116849    .0043197
               years_employ_agency |   .0048594   .0043662     1.11   0.266    -.0036983    .0134171
             years_employ_position |  -.0146796   .0065064    -2.26   0.024     -.027432   -.0019272
                                   |
                              pid5 |
                       Republican  |  -.0075283   .0879073    -0.09   0.932    -.1798234    .1647667
                  Lean Republican  |   .1034752   .1107926     0.93   0.350    -.1136743    .3206246
                  Lean Democratic  |   .1103128   .1026018     1.08   0.282    -.0907831    .3114086
                       Democratic  |   .0135405   .0806144     0.17   0.867    -.1444609    .1715419
                                   |
                       agency_size |
                           25-100  |   .1253792    .082296     1.52   0.128    -.0359181    .2866765
                          101-500  |   .1113537   .0902228     1.23   0.217    -.0654798    .2881871
                        501-1,000  |  -.0567738   .1147183    -0.49   0.621    -.2816174    .1680699
                      1,001-5,000  |  -.0761149   .1202271    -0.63   0.527    -.3117557    .1595259
                       Over 5,000  |  -.1235379   .1593125    -0.78   0.438    -.4357847    .1887089
                                   |
                 log_agency_budget |   .0213901   .0201369     1.06   0.288    -.0180776    .0608577
                      inst6017_nom |   .0042954   .0030176     1.42   0.155     -.001619    .0102098
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .2046437   .1788283     1.14   0.252    -.1458534    .5551408
                Staff: Non-Fiscal  |   .3076598   .1877534     1.64   0.101    -.0603302    .6756497
Income Security & Social Services  |   .1177084   .1701661     0.69   0.489    -.2158111    .4512279
                        Education  |   .1792549   .1800263     1.00   0.319    -.1735902    .5320999
                           Health  |   .2955524   .1775887     1.66   0.096     -.052515    .6436199
                Natural Resources  |   .3483279   .1612063     2.16   0.031     .0323693    .6642865
             Environment & Energy  |   .4479271   .1689325     2.65   0.008     .1168254    .7790287
             Economic Development  |   .1024516   .1730486     0.59   0.554    -.2367174    .4416207
                 Criminal Justice  |  -.0191502   .1736361    -0.11   0.912    -.3594706    .3211703
                       Regulatory  |   .0581362    .163277     0.36   0.722    -.2618808    .3781532
                   Transportation  |    .419045     .18057     2.32   0.020     .0651343    .7729556
                            Other  |   .2624282   .1740468     1.51   0.132    -.0786973    .6035537
                                   |
                             state |
                               AK  |   .1500455   .2278679     0.66   0.510    -.2965673    .5966584
                               AZ  |   .1653854   .2543597     0.65   0.516    -.3331505    .6639214
                               AR  |   .7699093   .2463026     3.13   0.002      .287165    1.252654
                               CA  |   .1439697   .2529657     0.57   0.569    -.3518339    .6397733
                               CO  |   .0123508   .2315014     0.05   0.957    -.4413835    .4660852
                               CT  |   .8887428    .299065     2.97   0.003      .302586    1.474899
                               DE  |   .2181934   .2333299     0.94   0.350    -.2391248    .6755117
                               FL  |   .5577931   .2538451     2.20   0.028     .0602658     1.05532
                               GA  |   .2323614   .2371192     0.98   0.327    -.2323837    .6971064
                               ID  |   .8556011   .2354221     3.63   0.000     .3941824     1.31702
                               IL  |   .3374832   .2554456     1.32   0.186     -.163181    .8381475
                               IN  |   .2363443   .2445784     0.97   0.334    -.2430206    .7157091
                               IA  |   .9037246   .2134575     4.23   0.000     .4853555    1.322094
                               KS  |   .9960677   .2450131     4.07   0.000     .5158509    1.476284
                               KY  |    1.02353   .2380906     4.30   0.000     .5568811    1.490179
                               LA  |   .4435183   .2583922     1.72   0.086     -.062921    .9499576
                               ME  |   .2810427   .2533677     1.11   0.267    -.2155489    .7776343
                               MD  |   .6243447   .2453202     2.55   0.011     .1435259    1.105164
                               MA  |  -.1497045    .237408    -0.63   0.528    -.6150156    .3156066
                               MI  |    .928044   .2381356     3.90   0.000     .4613068    1.394781
                               MN  |    .076711   .2230411     0.34   0.731    -.3604415    .5138634
                               MS  |   .4658031    .249386     1.87   0.062    -.0229845    .9545908
                               MO  |   .2383142   .2219223     1.07   0.283    -.1966456     .673274
                               MT  |   .0555883   .2221633     0.25   0.802    -.3798437    .4910203
                               NE  |   .2061234   .2430325     0.85   0.396    -.2702116    .6824584
                               NV  |   .3935328    .243113     1.62   0.106    -.0829599    .8700254
                               NH  |   1.116995   .2505615     4.46   0.000     .6259037    1.608087
                               NJ  |   .4525199   .2559937     1.77   0.077    -.0492185    .9542583
                               NM  |  -.3668666   .2481478    -1.48   0.139    -.8532273    .1194941
                               NY  |   .1919463   .2812679     0.68   0.495    -.3593287    .7432213
                               NC  |    .431317   .2260294     1.91   0.056    -.0116926    .8743266
                               ND  |   .2925143   .2297112     1.27   0.203    -.1577113      .74274
                               OH  |   .6608085   .2363941     2.80   0.005     .1974845    1.124133
                               OK  |   .8309937   .2346671     3.54   0.000     .3710547    1.290933
                               OR  |   .0834049   .2266073     0.37   0.713    -.3607373     .527547
                               PA  |   .2317778   .2446124     0.95   0.343    -.2476537    .7112094
                               RI  |    .049338   .2453476     0.20   0.841    -.4315346    .5302105
                               SC  |   1.106994   .2801232     3.95   0.000     .5579627    1.656025
                               SD  |    .225738   .2538049     0.89   0.374    -.2717104    .7231864
                               TN  |    .827056   .2415586     3.42   0.001     .3536098    1.300502
                               TX  |     .65718    .260324     2.52   0.012     .1469543    1.167406
                               UT  |   .4944746   .2237996     2.21   0.027     .0558355    .9331136
                               VT  |   .7824675   .2369683     3.30   0.001     .3180182    1.246917
                               VA  |    .410791   .2704819     1.52   0.129    -.1193438    .9409259
                               WA  |  -.1336515   .2278006    -0.59   0.557    -.5801325    .3128296
                               WV  |   1.077803   .2416141     4.46   0.000     .6042483    1.551358
                               WI  |   .8478946   .2226389     3.81   0.000     .4115305    1.284259
                               WY  |   .4298219   .2345564     1.83   0.067    -.0299001    .8895439
                                   |
                              year |
                             1984  |  -.2059874   .0942408    -2.19   0.029     -.390696   -.0212789
                             1988  |  -.1889896   .0919069    -2.06   0.040    -.3691238   -.0088555
                             1994  |   .0753578   .0959413     0.79   0.432    -.1126837    .2633992
                             1998  |   .2223611    .101718     2.19   0.029     .0229975    .4217248
                             2004  |  -.1887791   .1084705    -1.74   0.082    -.4013775    .0238192
                             2008  |   .1995805   .1124858     1.77   0.076    -.0208875    .4200486
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.697209   .7626333                     -3.191943   -.2024753
                             /cut2 |   .6488593    .759284                     -.8393099    2.137029
                             /cut3 |    2.29871   .7595389                      .8100407    3.787378
----------------------------------------------------------------------------------------------------

. est sto c8 

. 
.  esttab c1 c2 c3 c4 c5 c6 c7 c8 using Table_B4.rtf ,starlevels(+ 0.10 * 0.05 ** 0.01) cells(b(star fmt(3)) 
> se(par fmt(3))) ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Gov. Policy" "Legis. Policy" "Gov. Regs" "Legis. Regs" "Gov. Policy" "Legis. Policy" "Gov. Regs" 
> "Legis. Regs") 
(output written to Table_B4.rtf)

. 
. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B5 ******
. gen treated =1 if intersection==3
(11,331 missing values generated)

. replace treated=0 if intersection==0 
(7,126 real changes made)

. 
. drop if treated==. 
(4,205 observations deleted)

. cem   civil_service  age(#6) age_2(#6) edu(#0) funcat(#0), treatment(treated)

Matching Summary:
-----------------
Number of strata: 863
Number of matched strata: 111

              0     1
      All  7126   188
  Matched  2739   178
Unmatched  4387    10


Multivariate L1 distance: .59074324

Univariate imbalance:

                     L1      mean       min       25%       50%       75%       max
civil_service   2.6e-15  -7.8e-16         0         0         0         0         .
          age     .0966    -.1162         4         0        -1         0         .
        age_2    .08323   -11.856       224         0       -97         0         .
          edu   2.5e-15  -2.0e-14         0         0         0         0         .
       funcat   2.8e-15  -2.9e-14         0         0         0         0         0

. 
. 
. ologit reve_1a i.treated weekly_hours years_employ_state b3.pid5 agency_size log_agency_budget years_employ
> _agency years_employ_position inst6017_nom i.state i.year [iweight=cem_weights] , r

Iteration 0:   log pseudolikelihood = -3288.2184  
Iteration 1:   log pseudolikelihood = -2916.9741  
Iteration 2:   log pseudolikelihood = -2902.2078  
Iteration 3:   log pseudolikelihood =  -2902.172  
Iteration 4:   log pseudolikelihood =  -2902.172  

Ordered logistic regression                     Number of obs     =      2,506
                                                Wald chi2(68)     =     452.78
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -2902.172               Pseudo R2         =     0.1174

---------------------------------------------------------------------------------------
                      |               Robust
              reve_1a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            1.treated |  -.5497897   .1972062    -2.79   0.005    -.9363067   -.1632727
         weekly_hours |    .053098   .0072298     7.34   0.000     .0389278    .0672682
   years_employ_state |   .0013524   .0090893     0.15   0.882    -.0164624    .0191671
                      |
                 pid5 |
          Republican  |    .484215   .2033454     2.38   0.017     .0856654    .8827647
     Lean Republican  |   .0963619   .2357672     0.41   0.683    -.3657332    .5584571
     Lean Democratic  |   -.076201   .2377565    -0.32   0.749    -.5421953    .3897932
          Democratic  |   .4538169   .1799852     2.52   0.012     .1010525    .8065813
                      |
          agency_size |   .2893859   .0570123     5.08   0.000     .1776438    .4011279
    log_agency_budget |   .0810289   .0385962     2.10   0.036     .0053817    .1566761
  years_employ_agency |  -.0478381   .0095412    -5.01   0.000    -.0665385   -.0291377
years_employ_position |  -.0076413   .0148631    -0.51   0.607    -.0367724    .0214899
         inst6017_nom |  -.0082377   .0065894    -1.25   0.211    -.0211526    .0046772
                      |
                state |
                  AK  |  -1.402263   .9491251    -1.48   0.140    -3.262514    .4579878
                  AZ  |  -1.306746    .526816    -2.48   0.013    -2.339286   -.2742055
                  AR  |  -.9132897   .7643439    -1.19   0.232    -2.411376    .5847968
                  CA  |  -2.379361   .3613441    -6.58   0.000    -3.087583    -1.67114
                  CO  |    .389682   .5215291     0.75   0.455    -.6324963     1.41186
                  CT  |  -.6656463   .4400601    -1.51   0.130    -1.528148    .1968557
                  DE  |   -.530882    .431608    -1.23   0.219    -1.376818     .315054
                  FL  |  -1.339046   .4039562    -3.31   0.001    -2.130786   -.5473067
                  GA  |  -.9438391   .3921292    -2.41   0.016    -1.712398   -.1752801
                  HI  |  -.7507701   .5848045    -1.28   0.199    -1.896966    .3954256
                  ID  |   .9533467   .3944301     2.42   0.016      .180278    1.726415
                  IL  |  -1.347053   .3786308    -3.56   0.000    -2.089156   -.6049502
                  IN  |  -.4252271   .4217296    -1.01   0.313    -1.251802    .4013478
                  IA  |  -.6045152   .2913155    -2.08   0.038    -1.175483   -.0335472
                  KS  |  -.4459644   .3665737    -1.22   0.224    -1.164436    .2725068
                  KY  |  -1.068865   .4273808    -2.50   0.012    -1.906516   -.2312142
                  LA  |  -.6132598   .4366808    -1.40   0.160    -1.469138    .2426188
                  ME  |  -.2778296   .3894093    -0.71   0.476    -1.041058    .4853987
                  MD  |  -1.115549   .4623402    -2.41   0.016     -2.02172   -.2093793
                  MA  |  -1.509753   .3328047    -4.54   0.000    -2.162039   -.8574681
                  MI  |  -1.269476    .554386    -2.29   0.022    -2.356053   -.1828995
                  MN  |  -.3528595   .3779683    -0.93   0.351    -1.093664    .3879447
                  MS  |  -.5910027   .4770386    -1.24   0.215    -1.525981    .3439757
                  MO  |  -1.248189   .3410993    -3.66   0.000    -1.916731   -.5796463
                  MT  |  -.3241627   .4048781    -0.80   0.423    -1.117709    .4693837
                  NE  |   .2723011   .4537266     0.60   0.548    -.6169867    1.161589
                  NV  |  -1.208811   .5497961    -2.20   0.028    -2.286392   -.1312309
                  NH  |  -.2362609   .4174578    -0.57   0.571    -1.054463    .5819414
                  NJ  |  -.8304901   .4457682    -1.86   0.062     -1.70418    .0431995
                  NM  |   .9002354   .5844383     1.54   0.123    -.2452427    2.045713
                  NY  |  -1.880497   .5142153    -3.66   0.000    -2.888341   -.8726538
                  NC  |  -.8999237   .3529841    -2.55   0.011     -1.59176   -.2080876
                  ND  |    .716721    .454011     1.58   0.114    -.1731242    1.606566
                  OH  |  -.6377315   .3565552    -1.79   0.074    -1.336567     .061104
                  OK  |  -.6201817   .3465318    -1.79   0.074    -1.299371    .0590081
                  OR  |  -.2255446    .319177    -0.71   0.480      -.85112    .4000308
                  PA  |  -1.914195   .4378035    -4.37   0.000    -2.772274   -1.056116
                  RI  |  -.0757265   .3317093    -0.23   0.819    -.7258648    .5744118
                  SC  |  -.2040983   .3117843    -0.65   0.513    -.8151842    .4069876
                  SD  |   .4282051   .3308671     1.29   0.196    -.2202824    1.076693
                  TN  |  -.8059321   .3657461    -2.20   0.028    -1.522781   -.0890829
                  TX  |  -1.961739   .2821826    -6.95   0.000    -2.514807   -1.408672
                  UT  |  -.0075229   .3180258    -0.02   0.981    -.6308421    .6157962
                  VT  |  -.0110893    .477626    -0.02   0.981     -.947219    .9250404
                  VA  |  -1.288786   .2938745    -4.39   0.000     -1.86477   -.7128029
                  WA  |  -.3344897   .3413445    -0.98   0.327    -1.003513    .3345334
                  WV  |  -.0104121   .4293594    -0.02   0.981     -.851941    .8311169
                  WI  |  -.6693294   .4437149    -1.51   0.131    -1.538995    .2003357
                  WY  |   1.089696   .4056932     2.69   0.007     .2945517     1.88484
                      |
                 year |
                1978  |  -.4091204   .2176626    -1.88   0.060    -.8357313    .0174906
                1984  |  -.5734639   .2045908    -2.80   0.005    -.9744546   -.1724733
                1988  |  -.7698925   .2052169    -3.75   0.000     -1.17211   -.3676748
                1994  |  -.7086495   .2052179    -3.45   0.001    -1.110869   -.3064298
                1998  |  -.8410271   .2279842    -3.69   0.000    -1.287868   -.3941862
                2004  |  -.7375969   .2319602    -3.18   0.001    -1.192231   -.2829633
                2008  |  -.5357035   .2613112    -2.05   0.040    -1.047864   -.0235429
----------------------+----------------------------------------------------------------
                /cut1 |    .021091   .6041565                     -1.163034    1.205216
                /cut2 |   2.731373   .6035291                      1.548478    3.914269
                /cut3 |   4.099016   .6131256                      2.897312     5.30072
                /cut4 |   6.377034   .6606784                      5.082128     7.67194
---------------------------------------------------------------------------------------

. est sto d1

. ologit reve_1b i.treated weekly_hours years_employ_state b3.pid5 agency_size log_agency_budget years_employ
> _agency years_employ_position inst6017_nom i.state i.year [iweight=cem_weights] , r

Iteration 0:   log pseudolikelihood = -2902.6825  
Iteration 1:   log pseudolikelihood = -2631.8677  
Iteration 2:   log pseudolikelihood =  -2625.841  
Iteration 3:   log pseudolikelihood =  -2625.819  
Iteration 4:   log pseudolikelihood =  -2625.819  

Ordered logistic regression                     Number of obs     =      2,127
                                                Wald chi2(67)     =     384.90
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -2625.819               Pseudo R2         =     0.0954

---------------------------------------------------------------------------------------
                      |               Robust
              reve_1b |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            1.treated |  -.5306698   .1989913    -2.67   0.008    -.9206856   -.1406541
         weekly_hours |   .0524019   .0075679     6.92   0.000      .037569    .0672347
   years_employ_state |  -.0067156   .0098956    -0.68   0.497    -.0261106    .0126795
                      |
                 pid5 |
          Republican  |    .424784   .1930519     2.20   0.028     .0464092    .8031589
     Lean Republican  |  -.3222166   .2825984    -1.14   0.254    -.8760994    .2316662
     Lean Democratic  |    .008294   .2417507     0.03   0.973    -.4655286    .4821166
          Democratic  |   .3314317   .1898476     1.75   0.081    -.0406627    .7035261
                      |
          agency_size |   .1699827   .0665082     2.56   0.011      .039629    .3003364
    log_agency_budget |   .1193435   .0390602     3.06   0.002     .0427869       .1959
  years_employ_agency |  -.0369459   .0100476    -3.68   0.000    -.0566387    -.017253
years_employ_position |    .009536   .0148688     0.64   0.521    -.0196064    .0386783
         inst6017_nom |  -.0051703   .0076179    -0.68   0.497    -.0201012    .0097605
                      |
                state |
                  AK  |  -.2320948   .5353159    -0.43   0.665    -1.281295    .8171052
                  AZ  |  -.5062267   .4857087    -1.04   0.297    -1.458198    .4457449
                  AR  |   .3171281   .4831441     0.66   0.512     -.629817    1.264073
                  CA  |  -1.594308   .4114475    -3.87   0.000     -2.40073   -.7878855
                  CO  |   1.350471   .7559485     1.79   0.074    -.1311609    2.832103
                  CT  |  -.0169816   .5624385    -0.03   0.976    -1.119341    1.085378
                  DE  |  -1.077899   .4106024    -2.63   0.009    -1.882664   -.2731326
                  FL  |  -.6892642   .4995412    -1.38   0.168    -1.668347    .2898186
                  GA  |  -.4402845   .5096619    -0.86   0.388    -1.439203    .5586343
                  HI  |  -1.002494    .582387    -1.72   0.085    -2.143952    .1389633
                  ID  |   1.552264   .5128554     3.03   0.002     .5470863    2.557442
                  IL  |   .5921404   .8776672     0.67   0.500    -1.128056    2.312337
                  IN  |   .3929117    .516938     0.76   0.447    -.6202683    1.406092
                  IA  |  -.1849832   .3710494    -0.50   0.618    -.9122267    .5422603
                  KS  |   .1273656   .5004741     0.25   0.799    -.8535455    1.108277
                  KY  |  -.8997466    .484201    -1.86   0.063    -1.848763    .0492699
                  LA  |  -.0764723   .4726875    -0.16   0.871    -1.002923    .8499782
                  ME  |  -.0314061   .4462483    -0.07   0.944    -.9060367    .8432245
                  MD  |  -.4796227   .4834726    -0.99   0.321    -1.427212    .4679662
                  MA  |  -.2424113   .7042398    -0.34   0.731    -1.622696    1.137873
                  MI  |  -.4760571    .579412    -0.82   0.411    -1.611684    .6595695
                  MN  |  -.2583703   .4067662    -0.64   0.525    -1.055617    .5388768
                  MS  |  -1.112435   .5439926    -2.04   0.041    -2.178641   -.0462295
                  MO  |  -.8164605   .4156502    -1.96   0.049     -1.63112    -.001801
                  MT  |   .4952554   .4154038     1.19   0.233     -.318921    1.309432
                  NE  |   .1562317   .4596988     0.34   0.734    -.7447613    1.057225
                  NV  |  -1.398436   1.043536    -1.34   0.180    -3.443728    .6468571
                  NH  |  -.2189118   .4533971    -0.48   0.629    -1.107554    .6697301
                  NJ  |  -.4136417   .5748311    -0.72   0.472     -1.54029    .7130065
                  NM  |  -.2483646   .4339906    -0.57   0.567     -1.09897    .6022413
                  NY  |   .4683929   .5403689     0.87   0.386    -.5907107    1.527497
                  NC  |  -.8889267   .4378723    -2.03   0.042    -1.747141   -.0307127
                  ND  |   .2880916   .3891627     0.74   0.459    -.4746532    1.050836
                  OH  |  -.9452395   .4115485    -2.30   0.022     -1.75186   -.1386193
                  OK  |  -.4742215   .4220811    -1.12   0.261    -1.301485    .3530423
                  OR  |  -.1924918   .3931329    -0.49   0.624    -.9630181    .5780345
                  PA  |  -1.371764   .4883489    -2.81   0.005     -2.32891   -.4146178
                  RI  |  -.0226111   .5139743    -0.04   0.965    -1.029982      .98476
                  SC  |   .2401721   .4434651     0.54   0.588    -.6290035    1.109348
                  SD  |   .7753326   .6125535     1.27   0.206    -.4252502    1.975915
                  TN  |  -1.177405    .509896    -2.31   0.021    -2.176783   -.1780268
                  TX  |  -.8749337   .4166304    -2.10   0.036    -1.691514    -.058353
                  UT  |  -.4557582   .4951667    -0.92   0.357    -1.426267    .5147507
                  VT  |  -.0767027   .6298631    -0.12   0.903    -1.311212    1.157806
                  VA  |  -.9819639   .4194356    -2.34   0.019    -1.804043   -.1598852
                  WA  |  -.2034822   .4198378    -0.48   0.628    -1.026349    .6193847
                  WV  |   .5413194   .6602582     0.82   0.412    -.7527628    1.835402
                  WI  |  -.7948775   .5194463    -1.53   0.126    -1.812973    .2232185
                  WY  |   .4319598   .4584393     0.94   0.346    -.4665647    1.330484
                      |
                 year |
                1984  |   .0870067   .2142007     0.41   0.685     -.332819    .5068324
                1988  |   .1284748    .207643     0.62   0.536    -.2784981    .5354477
                1994  |   .0859319   .2249218     0.38   0.702    -.3549066    .5267705
                1998  |   .0630121    .222208     0.28   0.777    -.3725077    .4985319
                2004  |   .0729075   .2353322     0.31   0.757    -.3883352    .5341502
                2008  |  -.0556831    .272853    -0.20   0.838    -.5904652    .4790991
----------------------+----------------------------------------------------------------
                /cut1 |  -1.388109   .7378723                     -2.834312    .0580939
                /cut2 |   1.539732   .7099534                      .1482485    2.931215
                /cut3 |   2.843497   .7129651                      1.446111    4.240883
                /cut4 |   4.757788   .7252101                      3.336402    6.179174
---------------------------------------------------------------------------------------

. est sto d2

. ologit reve_1c i.treated weekly_hours years_employ_state b3.pid5 agency_size log_agency_budget years_employ
> _agency years_employ_position inst6017_nom i.state i.year [iweight=cem_weights] , r

Iteration 0:   log pseudolikelihood = -3346.6843  
Iteration 1:   log pseudolikelihood = -3024.1363  
Iteration 2:   log pseudolikelihood = -3017.7371  
Iteration 3:   log pseudolikelihood = -3017.7233  
Iteration 4:   log pseudolikelihood = -3017.7233  

Ordered logistic regression                     Number of obs     =      2,505
                                                Wald chi2(68)     =     430.95
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -3017.7233               Pseudo R2         =     0.0983

---------------------------------------------------------------------------------------
                      |               Robust
              reve_1c |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            1.treated |  -.5750889   .2033642    -2.83   0.005    -.9736755   -.1765024
         weekly_hours |   .0406102   .0087962     4.62   0.000     .0233699    .0578505
   years_employ_state |   .0052351   .0096131     0.54   0.586    -.0136062    .0240764
                      |
                 pid5 |
          Republican  |   .1103856    .178685     0.62   0.537    -.2398306    .4606017
     Lean Republican  |  -.2303091   .2570784    -0.90   0.370    -.7341736    .2735554
     Lean Democratic  |  -.0654646   .2136942    -0.31   0.759    -.4842975    .3533683
          Democratic  |   .1582307   .1689283     0.94   0.349    -.1728628    .4893241
                      |
          agency_size |   .1550927    .058894     2.63   0.008     .0396625     .270523
    log_agency_budget |   .1458862   .0416223     3.50   0.000     .0643079    .2274644
  years_employ_agency |  -.0195635   .0093643    -2.09   0.037    -.0379172   -.0012097
years_employ_position |   .0047509   .0139972     0.34   0.734    -.0226831    .0321848
         inst6017_nom |  -.0069431   .0063326    -1.10   0.273    -.0193547    .0054685
                      |
                state |
                  AK  |   .0510815   .8023797     0.06   0.949    -1.521554    1.623717
                  AZ  |   .6889907   .4692516     1.47   0.142    -.2307254    1.608707
                  AR  |   1.246927   .5250282     2.37   0.018      .217891    2.275964
                  CA  |   1.053406   1.336255     0.79   0.431    -1.565605    3.672417
                  CO  |   .6446069   .5745464     1.12   0.262    -.4814833    1.770697
                  CT  |   1.375964   .4778587     2.88   0.004     .4393781     2.31255
                  DE  |   .4604651   .4986683     0.92   0.356    -.5169068    1.437837
                  FL  |   .0997588   .5193182     0.19   0.848    -.9180862    1.117604
                  GA  |   1.116061   .4852943     2.30   0.021     .1649021    2.067221
                  HI  |   .0552065   .5552151     0.10   0.921    -1.032995    1.143408
                  ID  |   .6242805   .6471808     0.96   0.335    -.6441705    1.892732
                  IL  |   1.823039   .6503694     2.80   0.005     .5483384     3.09774
                  IN  |  -.4035851   .4898627    -0.82   0.410    -1.363698    .5565282
                  IA  |   .3293654   .4777814     0.69   0.491    -.6070689      1.2658
                  KS  |   1.296616   .4698069     2.76   0.006     .3758118    2.217421
                  KY  |  -.0201594   .5532343    -0.04   0.971    -1.104479     1.06416
                  LA  |   1.084516   .6836086     1.59   0.113    -.2553322    2.424364
                  ME  |   1.502175    .428308     3.51   0.000     .6627066    2.341643
                  MD  |   1.114605   .4814174     2.32   0.021     .1710447    2.058166
                  MA  |   .5778837   .4598409     1.26   0.209    -.3233879    1.479155
                  MI  |   .6056804   .6511448     0.93   0.352      -.67054    1.881901
                  MN  |   1.068036   .4373349     2.44   0.015     .2108752    1.925197
                  MS  |  -.4350697   .6854903    -0.63   0.526    -1.778606    .9084666
                  MO  |   .9892237   .4468668     2.21   0.027     .1133808    1.865067
                  MT  |  -.2151373   .5920296    -0.36   0.716    -1.375494    .9452194
                  NE  |   .8101163   .5006127     1.62   0.106    -.1710667    1.791299
                  NV  |  -.7683233   .7379338    -1.04   0.298    -2.214647    .6780003
                  NH  |   1.272795   .4551681     2.80   0.005     .3806815    2.164908
                  NJ  |   .5557828   .6447728     0.86   0.389    -.7079488    1.819514
                  NM  |  -.1620403   .4699252    -0.34   0.730    -1.083077    .7589962
                  NY  |  -.1531899   .5523509    -0.28   0.782    -1.235778    .9293981
                  NC  |   .3069371   .4519643     0.68   0.497    -.5788967    1.192771
                  ND  |    .497811   .4712204     1.06   0.291     -.425764    1.421386
                  OH  |    .119375   .4570573     0.26   0.794    -.7764407    1.015191
                  OK  |   1.519472   .4602129     3.30   0.001     .6174714    2.421473
                  OR  |   .1338802   .4868385     0.27   0.783    -.8203057    1.088066
                  PA  |   .6356443   .4891613     1.30   0.194    -.3230942    1.594383
                  RI  |   .0053116    .435071     0.01   0.990    -.8474119    .8580351
                  SC  |   1.722537   .4990326     3.45   0.001     .7444506    2.700622
                  SD  |   .1224366    .537971     0.23   0.820    -.9319672     1.17684
                  TN  |   .7595474   .4950303     1.53   0.125    -.2106942    1.729789
                  TX  |    1.10342   .5909131     1.87   0.062     -.054748    2.261589
                  UT  |  -.3916826   .4876184    -0.80   0.422    -1.347397    .5640319
                  VT  |   1.479986   .5439705     2.72   0.007     .4138235    2.546148
                  VA  |  -.1190415   .4660161    -0.26   0.798    -1.032416    .7943333
                  WA  |   .0097599   .6649089     0.01   0.988    -1.293438    1.312958
                  WV  |   .6751081   .4822384     1.40   0.162    -.2700618    1.620278
                  WI  |   .4919091   .6120597     0.80   0.422    -.7077058    1.691524
                  WY  |  -.5560527   .4403796    -1.26   0.207    -1.419181    .3070754
                      |
                 year |
                1978  |  -.2377323   .2285002    -1.04   0.298    -.6855844    .2101199
                1984  |  -.0602049   .2362956    -0.25   0.799    -.5233357    .4029259
                1988  |  -.1030627   .2065091    -0.50   0.618    -.5078131    .3016878
                1994  |  -.0391211   .2304896    -0.17   0.865    -.4908724    .4126302
                1998  |  -.3220317   .2091046    -1.54   0.124    -.7318693    .0878058
                2004  |  -.6779352   .2350381    -2.88   0.004    -1.138601    -.217269
                2008  |  -.5864311   .2978458    -1.97   0.049    -1.170198    -.002664
----------------------+----------------------------------------------------------------
                /cut1 |  -1.794114   .7646713                     -3.292842    -.295386
                /cut2 |   1.827959   .7054547                      .4452934    3.210625
                /cut3 |   3.336439   .7153339                       1.93441    4.738468
                /cut4 |   5.463333   .7295695                      4.033403    6.893263
---------------------------------------------------------------------------------------

. est sto d3

. ologit reve_1d i.treated weekly_hours years_employ_state b3.pid5 agency_size log_agency_budget years_employ
> _agency years_employ_position inst6017_nom i.state i.year [iweight=cem_weights] , r

Iteration 0:   log pseudolikelihood = -2790.2208  
Iteration 1:   log pseudolikelihood = -2537.7269  
Iteration 2:   log pseudolikelihood = -2532.1486  
Iteration 3:   log pseudolikelihood = -2532.1319  
Iteration 4:   log pseudolikelihood = -2532.1319  

Ordered logistic regression                     Number of obs     =      2,121
                                                Wald chi2(67)     =     285.13
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2532.1319               Pseudo R2         =     0.0925

---------------------------------------------------------------------------------------
                      |               Robust
              reve_1d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            1.treated |  -.6628106   .2432271    -2.73   0.006    -1.139527   -.1860942
         weekly_hours |   .0247182   .0074264     3.33   0.001     .0101628    .0392736
   years_employ_state |   .0125122     .00904     1.38   0.166     -.005206    .0302303
                      |
                 pid5 |
          Republican  |   .0439688   .1890853     0.23   0.816    -.3266315    .4145692
     Lean Republican  |  -.5904792   .2857579    -2.07   0.039    -1.150554    -.030404
     Lean Democratic  |  -.1455409   .2492974    -0.58   0.559    -.6341549    .3430731
          Democratic  |  -.0403692   .1702046    -0.24   0.813    -.3739641    .2932257
                      |
          agency_size |   .0002361   .0601893     0.00   0.997    -.1177328     .118205
    log_agency_budget |    .106899   .0433136     2.47   0.014     .0220059    .1917921
  years_employ_agency |  -.0031141   .0094104    -0.33   0.741     -.021558    .0153299
years_employ_position |  -.0123272   .0122555    -1.01   0.314    -.0363476    .0116932
         inst6017_nom |   .0094062   .0080191     1.17   0.241     -.006311    .0251234
                      |
                state |
                  AK  |   3.064358   .8016716     3.82   0.000     1.493111    4.635606
                  AZ  |   2.647834    .785465     3.37   0.001     1.108351    4.187317
                  AR  |   1.763912   .7354335     2.40   0.016     .3224885    3.205335
                  CA  |   2.277072   1.022533     2.23   0.026     .2729441      4.2812
                  CO  |   2.181371   .9018931     2.42   0.016     .4136933    3.949049
                  CT  |   2.110538    .733877     2.88   0.004     .6721658    3.548911
                  DE  |   .9482058   .7714543     1.23   0.219    -.5638167    2.460228
                  FL  |   2.430099   .7702929     3.15   0.002     .9203527    3.939845
                  GA  |   1.978275   .7491285     2.64   0.008     .5100105     3.44654
                  HI  |   1.290818   .7762836     1.66   0.096    -.2306704    2.812305
                  ID  |   2.025014   .7802817     2.60   0.009     .4956899    3.554338
                  IL  |   2.534737   .8165537     3.10   0.002     .9343215    4.135153
                  IN  |   .9120846   .8123842     1.12   0.262    -.6801592    2.504328
                  IA  |   1.503966   .7481764     2.01   0.044     .0375668    2.970364
                  KS  |   3.374499   .7586805     4.45   0.000     1.887513    4.861486
                  KY  |     1.3332   .7562674     1.76   0.078    -.1490568    2.815457
                  LA  |    2.61583   .8385551     3.12   0.002     .9722922    4.259368
                  ME  |   2.835465   .7437823     3.81   0.000     1.377678    4.293251
                  MD  |   2.213614   .7494603     2.95   0.003     .7446986    3.682529
                  MA  |   1.875544   .7967201     2.35   0.019     .3140013    3.437087
                  MI  |   2.976577   1.112529     2.68   0.007     .7960601    5.157094
                  MN  |   2.724466   .9666697     2.82   0.005     .8298277    4.619103
                  MS  |    .798143   .8329159     0.96   0.338    -.8343423    2.430628
                  MO  |   1.962472   .7269965     2.70   0.007      .537585    3.387359
                  MT  |   1.524546   .8981748     1.70   0.090     -.235844    3.284936
                  NE  |   2.372012   .7466417     3.18   0.001     .9086216    3.835403
                  NV  |   1.638441   .7050569     2.32   0.020      .256555    3.020327
                  NH  |   2.047782   .7543811     2.71   0.007     .5692226    3.526342
                  NJ  |   2.196251   .8100832     2.71   0.007      .608517    3.783985
                  NM  |   .7775567   .9613732     0.81   0.419      -1.1067    2.661814
                  NY  |   1.471062   .8480753     1.73   0.083    -.1911355    3.133259
                  NC  |   1.472396     .72864     2.02   0.043     .0442879    2.900504
                  ND  |   .7468989   .7390525     1.01   0.312    -.7016174    2.195415
                  OH  |   2.424398   .7551737     3.21   0.001     .9442851    3.904511
                  OK  |   2.898444    .764677     3.79   0.000     1.399705    4.397183
                  OR  |   2.025123   .7561351     2.68   0.007     .5431252     3.50712
                  PA  |   2.392344    .772777     3.10   0.002     .8777284    3.906959
                  RI  |   1.005674   .7410429     1.36   0.175    -.4467434    2.458091
                  SC  |   3.122264   .7946911     3.93   0.000     1.564698     4.67983
                  SD  |    .651404   .7417374     0.88   0.380    -.8023745    2.105183
                  TN  |   1.838843    .744316     2.47   0.013     .3800105    3.297676
                  TX  |   3.455615   .8366471     4.13   0.000     1.815817    5.095413
                  UT  |   1.843658   .7540057     2.45   0.014     .3658344    3.321483
                  VT  |   1.561203   .7507552     2.08   0.038     .0897494    3.032656
                  VA  |   2.098851   .7826815     2.68   0.007     .5648231    3.632878
                  WA  |   1.710036   .7593921     2.25   0.024     .2216552    3.198418
                  WV  |   1.053875    .788565     1.34   0.181     -.491684    2.599434
                  WI  |   2.705629   .7898104     3.43   0.001     1.157629    4.253629
                  WY  |   .4720346   .7967103     0.59   0.554    -1.089489    2.033558
                      |
                 year |
                1984  |   .0188778   .2006094     0.09   0.925    -.3743094    .4120651
                1988  |   .3822514   .1917001     1.99   0.046     .0065262    .7579767
                1994  |   .2855518   .2195054     1.30   0.193    -.1446708    .7157744
                1998  |   .1086754   .2134374     0.51   0.611    -.3096542     .527005
                2004  |  -.6614189   .2126685    -3.11   0.002    -1.078241   -.2445962
                2008  |    .244525   .2612812     0.94   0.349    -.2675768    .7566268
----------------------+----------------------------------------------------------------
                /cut1 |  -.0242744   .9472142                      -1.88078    1.832231
                /cut2 |   3.056518   .9099219                      1.273104    4.839932
                /cut3 |   4.601027   .9115406                      2.814441    6.387614
                /cut4 |   6.943687   .9140143                      5.152251    8.735122
---------------------------------------------------------------------------------------

. est sto d4

. ologit d_15a i.treated weekly_hours years_employ_state b3.pid5 agency_size log_agency_budget years_employ_a
> gency years_employ_position inst6017_nom i.state i.year [iweight=cem_weights] , r

Iteration 0:   log pseudolikelihood = -1991.9061  
Iteration 1:   log pseudolikelihood = -1829.1606  
Iteration 2:   log pseudolikelihood = -1821.2772  
Iteration 3:   log pseudolikelihood = -1821.2303  
Iteration 4:   log pseudolikelihood = -1821.2303  

Ordered logistic regression                     Number of obs     =      2,118
                                                Wald chi2(67)     =     198.10
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -1821.2303               Pseudo R2         =     0.0857

---------------------------------------------------------------------------------------
                      |               Robust
                d_15a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            1.treated |   .4763688   .2523379     1.89   0.059    -.0182044     .970942
         weekly_hours |   .0158184   .0078314     2.02   0.043     .0004692    .0311676
   years_employ_state |   .0150311   .0119132     1.26   0.207    -.0083183    .0383805
                      |
                 pid5 |
          Republican  |   .0338042   .2114495     0.16   0.873    -.3806291    .4482375
     Lean Republican  |  -.6732827   .3074283    -2.19   0.029    -1.275831   -.0707342
     Lean Democratic  |  -.3437568   .2401486    -1.43   0.152    -.8144394    .1269259
          Democratic  |  -.1449002   .1938235    -0.75   0.455    -.5247874    .2349869
                      |
          agency_size |   .0073347   .0562489     0.13   0.896    -.1029112    .1175805
    log_agency_budget |   .0909621   .0406579     2.24   0.025     .0112741    .1706501
  years_employ_agency |  -.0372278      .0118    -3.15   0.002    -.0603554   -.0141002
years_employ_position |   -.021622   .0146611    -1.47   0.140    -.0503572    .0071132
         inst6017_nom |  -.0147978   .0078429    -1.89   0.059    -.0301695    .0005739
                      |
                state |
                  AK  |   .7354459   .6707235     1.10   0.273    -.5791481     2.05004
                  AZ  |   .7751624   .6215075     1.25   0.212    -.4429699    1.993295
                  AR  |   2.030905   .8646748     2.35   0.019     .3361737    3.725637
                  CA  |   2.774423   .9187229     3.02   0.003     .9737594    4.575087
                  CO  |   1.038657   .8110591     1.28   0.200    -.5509895    2.628304
                  CT  |   .8500263    .648303     1.31   0.190    -.4206241    2.120677
                  DE  |   1.604523   .6278696     2.56   0.011     .3739214    2.835125
                  FL  |   .2445499   .7170446     0.34   0.733    -1.160832    1.649932
                  GA  |   .8596263    .613554     1.40   0.161    -.3429174     2.06217
                  HI  |   1.350608   .6964984     1.94   0.052    -.0145042    2.715719
                  ID  |    .966968   .6774002     1.43   0.153     -.360712    2.294648
                  IL  |   1.623181   .7283839     2.23   0.026     .1955748    3.050787
                  IN  |    1.22521   .6443206     1.90   0.057    -.0376349    2.488055
                  IA  |   1.056818   .6520185     1.62   0.105    -.2211146    2.334751
                  KS  |   1.057649   .6124299     1.73   0.084    -.1426921    2.257989
                  KY  |   1.504884   .6232208     2.41   0.016     .2833939    2.726374
                  LA  |   1.950589   .7650478     2.55   0.011     .4511225    3.450055
                  ME  |   2.134253    .724561     2.95   0.003     .7141394    3.554366
                  MD  |   .9987979   .6306821     1.58   0.113    -.2373163    2.234912
                  MA  |   .9958285   .6396387     1.56   0.120    -.2578404    2.249497
                  MI  |   1.479295   .7195157     2.06   0.040     .0690699     2.88952
                  MN  |   1.978842   .7342871     2.69   0.007     .5396657    3.418018
                  MS  |   .1995005   .7301188     0.27   0.785    -1.231506    1.630507
                  MO  |   .8428038   .6170097     1.37   0.172    -.3665131    2.052121
                  MT  |   1.496189   .6842692     2.19   0.029     .1550455    2.837332
                  NE  |   1.113439   .6181792     1.80   0.072    -.0981698    2.325048
                  NV  |    1.87937   .7629738     2.46   0.014     .3839692    3.374771
                  NH  |   1.669742   .6576223     2.54   0.011     .3808259    2.958658
                  NJ  |    2.32015   .7982507     2.91   0.004     .7556073    3.884693
                  NM  |   .2234899   .7839512     0.29   0.776    -1.313026    1.760006
                  NY  |   2.370858     .71271     3.33   0.001     .9739721    3.767744
                  NC  |   1.070685   .6792987     1.58   0.115    -.2607157    2.402086
                  ND  |   .9555065   .6246963     1.53   0.126    -.2688757    2.179889
                  OH  |   .9728665   .7238323     1.34   0.179    -.4458188    2.391552
                  OK  |   .5233279   .5825207     0.90   0.369    -.6183917    1.665047
                  OR  |   .7553198   .6069797     1.24   0.213    -.4343384    1.944978
                  PA  |   1.188881   .5917095     2.01   0.045     .0291521    2.348611
                  RI  |   1.955945   .6732105     2.91   0.004     .6364767    3.275414
                  SC  |  -.1440372   .6337994    -0.23   0.820    -1.386261    1.098187
                  SD  |   1.652312    .714003     2.31   0.021     .2528923    3.051732
                  TN  |   1.405605   .6325709     2.22   0.026     .1657886    2.645421
                  TX  |  -.8404415   .6051769    -1.39   0.165    -2.026566    .3456835
                  UT  |   .8185433    .616064     1.33   0.184      -.38892    2.026007
                  VT  |   1.817275   .7083212     2.57   0.010     .4289911    3.205559
                  VA  |   .1103754   .6353012     0.17   0.862    -1.134792    1.355543
                  WA  |   1.293635   .7058319     1.83   0.067    -.0897706     2.67704
                  WV  |   1.304268   .6860212     1.90   0.057    -.0403084    2.648845
                  WI  |   1.414949   .6440003     2.20   0.028     .1527316    2.677166
                  WY  |    1.18662   .6906839     1.72   0.086    -.1670961    2.540335
                      |
                 year |
                1984  |   .0448268   .2301486     0.19   0.846    -.4062561    .4959097
                1988  |   .0347657   .2260914     0.15   0.878    -.4083653    .4778968
                1994  |    .571577   .2378002     2.40   0.016     .1054972    1.037657
                1998  |   .6124498   .2430717     2.52   0.012      .136038    1.088862
                2004  |    .230218   .2463169     0.93   0.350    -.2525541    .7129902
                2008  |   .2647784   .2794142     0.95   0.343    -.2828634    .8124203
----------------------+----------------------------------------------------------------
                /cut1 |  -2.739514    .962621                     -4.626217   -.8528118
                /cut2 |   -.680454   .8689383                     -2.383542    1.022634
                /cut3 |   .9530599   .8624219                      -.737256    2.643376
---------------------------------------------------------------------------------------

. est sto d5

. ologit d_16a i.treated weekly_hours years_employ_state b3.pid5 agency_size log_agency_budget years_employ_a
> gency years_employ_position inst6017_nom i.state i.year [iweight=cem_weights] , r

Iteration 0:   log pseudolikelihood = -2220.1273  
Iteration 1:   log pseudolikelihood = -2070.2627  
Iteration 2:   log pseudolikelihood = -2067.8213  
Iteration 3:   log pseudolikelihood = -2067.8165  
Iteration 4:   log pseudolikelihood = -2067.8165  

Ordered logistic regression                     Number of obs     =      2,118
                                                Wald chi2(67)     =     192.36
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2067.8165               Pseudo R2         =     0.0686

---------------------------------------------------------------------------------------
                      |               Robust
                d_16a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            1.treated |   .5812057   .2454691     2.37   0.018     .1000951    1.062316
         weekly_hours |   .0127902   .0077857     1.64   0.100    -.0024695      .02805
   years_employ_state |   .0110642   .0102788     1.08   0.282    -.0090819    .0312103
                      |
                 pid5 |
          Republican  |  -.4303712   .1949321    -2.21   0.027    -.8124312   -.0483113
     Lean Republican  |  -.5407384   .3126987    -1.73   0.084    -1.153617    .0721397
     Lean Democratic  |   .2196687   .2602038     0.84   0.399    -.2903214    .7296588
          Democratic  |  -.1659235   .1875111    -0.88   0.376    -.5334386    .2015915
                      |
          agency_size |  -.0672664   .0579625    -1.16   0.246    -.1808708    .0463381
    log_agency_budget |   .1149968   .0416644     2.76   0.006      .033336    .1966575
  years_employ_agency |  -.0083297   .0109008    -0.76   0.445    -.0296948    .0130354
years_employ_position |  -.0108674   .0156233    -0.70   0.487    -.0414885    .0197536
         inst6017_nom |   .0117763   .0076329     1.54   0.123     -.003184    .0267365
                      |
                state |
                  AK  |    1.69089   .8561812     1.97   0.048     .0128055    3.368974
                  AZ  |   2.026808   .8841123     2.29   0.022     .2939795    3.759636
                  AR  |   .0723188   .9108013     0.08   0.937    -1.712819    1.857457
                  CA  |   1.640291   .8997455     1.82   0.068    -.1231775     3.40376
                  CO  |   1.191662   .9514349     1.25   0.210    -.6731164     3.05644
                  CT  |   1.104835   .8811964     1.25   0.210    -.6222777    2.831949
                  DE  |   1.808295   .8597065     2.10   0.035     .1233016    3.493289
                  FL  |   2.302838   .9104964     2.53   0.011     .5182982    4.087378
                  GA  |   1.290811   .8830191     1.46   0.144    -.4398751    3.021496
                  HI  |   1.615615   .9107516     1.77   0.076    -.1694252    3.400656
                  ID  |   1.935369   .9288847     2.08   0.037     .1147888     3.75595
                  IL  |     1.2787   .8539341     1.50   0.134    -.3949798    2.952381
                  IN  |   .8188623   .8522173     0.96   0.337    -.8514528    2.489178
                  IA  |   1.958644   .8707638     2.25   0.024     .2519779    3.665309
                  KS  |   2.056652   .8508584     2.42   0.016     .3890001    3.724304
                  KY  |   1.281979    .934951     1.37   0.170    -.5504913    3.114449
                  LA  |    2.07698   1.037925     2.00   0.045     .0426833    4.111276
                  ME  |   2.815115   .9554608     2.95   0.003     .9424462    4.687784
                  MD  |    .472575   .8836876     0.53   0.593    -1.259421    2.204571
                  MA  |   .3277521   .8742827     0.37   0.708    -1.385811    2.041315
                  MI  |  -.1693419   .9952743    -0.17   0.865    -2.120044     1.78136
                  MN  |   2.533403   .9084379     2.79   0.005     .7528972    4.313908
                  MS  |   1.481201    .990427     1.50   0.135    -.4600001    3.422403
                  MO  |   .8239849   .8489234     0.97   0.332    -.8398745    2.487844
                  MT  |   1.597777    .872879     1.83   0.067    -.1130343    3.308588
                  NE  |   1.688135   .8900849     1.90   0.058    -.0563996    3.432669
                  NV  |   1.499741   .8785905     1.71   0.088    -.2222642    3.221747
                  NH  |   2.308433   .8451189     2.73   0.006       .65203    3.964835
                  NJ  |   1.294061   .9752106     1.33   0.185    -.6173169    3.205438
                  NM  |  -.1632565   1.111646    -0.15   0.883    -2.342043     2.01553
                  NY  |   1.582021   .8790231     1.80   0.072    -.1408331    3.304874
                  NC  |   1.366759   .8850765     1.54   0.123    -.3679588    3.101477
                  ND  |   2.502741   .8605337     2.91   0.004     .8161262    4.189356
                  OH  |   1.758791   .9547588     1.84   0.065    -.1125016    3.630084
                  OK  |    2.44628   .8911425     2.75   0.006     .6996726    4.192887
                  OR  |   2.606128     .88708     2.94   0.003     .8674829    4.344772
                  PA  |   .8761999    .854183     1.03   0.305     -.797968    2.550368
                  RI  |   .6742179    .919478     0.73   0.463    -1.127926    2.476362
                  SC  |   1.592823   .8824641     1.80   0.071    -.1367745    3.322421
                  SD  |   .8076096   .8085429     1.00   0.318    -.7771054    2.392325
                  TN  |   1.282648   .8839865     1.45   0.147    -.4499338    3.015229
                  TX  |    1.47607   .8706913     1.70   0.090    -.2304534    3.182594
                  UT  |   2.077571   .8615537     2.41   0.016     .3889565    3.766185
                  VT  |   1.741083   .8690621     2.00   0.045     .0377527    3.444413
                  VA  |   1.449908   .8569809     1.69   0.091    -.2297442    3.129559
                  WA  |   .8824202   .8824482     1.00   0.317    -.8471465    2.611987
                  WV  |   .8492402   .9001524     0.94   0.345     -.915026    2.613506
                  WI  |   1.911428   .8783949     2.18   0.030     .1898052     3.63305
                  WY  |   2.121585   .8807964     2.41   0.016     .3952562    3.847915
                      |
                 year |
                1984  |  -.1644391   .2205546    -0.75   0.456    -.5967181    .2678399
                1988  |   .1750861    .208041     0.84   0.400    -.2326667     .582839
                1994  |   .1608903   .2255803     0.71   0.476     -.281239    .6030197
                1998  |   .6132046   .2337389     2.62   0.009     .1550849    1.071324
                2004  |   .2503629   .2492061     1.00   0.315    -.2380721    .7387979
                2008  |   .5122333   .2917608     1.76   0.079    -.0596074    1.084074
----------------------+----------------------------------------------------------------
                /cut1 |  -1.046757   1.066671                     -3.137394    1.043879
                /cut2 |   1.299762   1.007109                     -.6741352    3.273659
                /cut3 |   3.300762   1.009574                      1.322033     5.27949
---------------------------------------------------------------------------------------

. est sto d6

. ologit d_20a i.treated weekly_hours years_employ_state b3.pid5 agency_size log_agency_budget years_employ_a
> gency years_employ_position inst6017_nom i.state i.year [iweight=cem_weights] , r

Iteration 0:   log pseudolikelihood = -2552.4199  
Iteration 1:   log pseudolikelihood = -2418.4018  
Iteration 2:   log pseudolikelihood = -2417.2632  
Iteration 3:   log pseudolikelihood = -2417.2619  
Iteration 4:   log pseudolikelihood = -2417.2619  

Ordered logistic regression                     Number of obs     =      2,093
                                                Wald chi2(67)     =     153.26
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2417.2619               Pseudo R2         =     0.0530

---------------------------------------------------------------------------------------
                      |               Robust
                d_20a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            1.treated |   .4209397   .2211905     1.90   0.057    -.0125856    .8544651
         weekly_hours |   .0071533   .0076653     0.93   0.351    -.0078704     .022177
   years_employ_state |   .0068542   .0089011     0.77   0.441    -.0105915       .0243
                      |
                 pid5 |
          Republican  |    .041768   .1994839     0.21   0.834    -.3492132    .4327492
     Lean Republican  |  -.4950339   .2885986    -1.72   0.086    -1.060677     .070609
     Lean Democratic  |   .2224743   .2492158     0.89   0.372    -.2659797    .7109283
          Democratic  |  -.0539504     .18079    -0.30   0.765    -.4082923    .3003916
                      |
          agency_size |  -.1524076   .0577249    -2.64   0.008    -.2655463   -.0392688
    log_agency_budget |   .1427318   .0363527     3.93   0.000     .0714817    .2139818
  years_employ_agency |   -.016503     .00948    -1.74   0.082    -.0350835    .0020774
years_employ_position |  -.0215552   .0118152    -1.82   0.068    -.0447126    .0016022
         inst6017_nom |  -.0085091   .0068264    -1.25   0.213    -.0218886    .0048704
                      |
                state |
                  AK  |   1.244859    .829552     1.50   0.133    -.3810331    2.870751
                  AZ  |   1.694595   .6603013     2.57   0.010     .4004285    2.988762
                  AR  |   1.059497    .589468     1.80   0.072    -.0958386    2.214833
                  CA  |   3.294437   .8419464     3.91   0.000     1.644252    4.944622
                  CO  |   1.477654   .6657538     2.22   0.026     .1728004    2.782507
                  CT  |   .6344407   .6098779     1.04   0.298    -.5608981    1.829779
                  DE  |   1.405924   .5531048     2.54   0.011      .321858    2.489989
                  FL  |   .9630834   .5647096     1.71   0.088    -.1437272    2.069894
                  GA  |   1.359362   .5598146     2.43   0.015     .2621458    2.456579
                  HI  |   2.277955   .6388806     3.57   0.000     1.025772    3.530138
                  ID  |   1.531565   .7106109     2.16   0.031     .1387929    2.924336
                  IL  |   2.317199    .758557     3.05   0.002     .8304545    3.803943
                  IN  |   2.110966   .5818724     3.63   0.000     .9705172    3.251415
                  IA  |   .9833197   .5516132     1.78   0.075    -.0978224    2.064462
                  KS  |   .8627175   .6271973     1.38   0.169    -.3665666    2.092001
                  KY  |   2.464497   .7736401     3.19   0.001     .9481902    3.980804
                  LA  |   2.393155   .8019493     2.98   0.003     .8213636    3.964947
                  ME  |   1.425211   .5907954     2.41   0.016     .2672734    2.583149
                  MD  |   1.095823   .5522701     1.98   0.047     .0133935    2.178253
                  MA  |   1.842664   .6761112     2.73   0.006     .5175101    3.167818
                  MI  |    1.37831   .7146508     1.93   0.054    -.0223803    2.778999
                  MN  |   1.240729   .6329646     1.96   0.050     .0001413    2.481317
                  MS  |   1.405696   .7337321     1.92   0.055    -.0323922    2.843785
                  MO  |   1.165798   .5988235     1.95   0.052    -.0078743    2.339471
                  MT  |   1.474323   .5751556     2.56   0.010     .3470391    2.601608
                  NE  |   1.516542   .5669663     2.67   0.007     .4053089    2.627776
                  NV  |    2.24562   .8304742     2.70   0.007     .6179206     3.87332
                  NH  |    1.17541   .6127073     1.92   0.055    -.0254741    2.376295
                  NJ  |   1.748943    .630757     2.77   0.006     .5126823    2.985204
                  NM  |   .5835092    .769831     0.76   0.448    -.9253319     2.09235
                  NY  |   1.842757   .6890346     2.67   0.007      .492274     3.19324
                  NC  |   .9923563   .6013119     1.65   0.099    -.1861934    2.170906
                  ND  |   1.036541   .5840681     1.77   0.076     -.108211    2.181294
                  OH  |   1.815718   .7755708     2.34   0.019     .2956269    3.335808
                  OK  |   1.677608   .5629806     2.98   0.003     .5741863     2.78103
                  OR  |   1.246831   .5753333     2.17   0.030      .119199    2.374464
                  PA  |   2.015759   .5842939     3.45   0.001     .8705643    3.160955
                  RI  |   1.742151   .6352952     2.74   0.006     .4969949    2.987306
                  SC  |   .6649326   .5484608     1.21   0.225    -.4100308    1.739896
                  SD  |   1.889617   .5492058     3.44   0.001     .8131933     2.96604
                  TN  |   1.778344   .5951455     2.99   0.003       .61188    2.944808
                  TX  |    .729726   .5600837     1.30   0.193    -.3680178     1.82747
                  UT  |   1.239957   .6002793     2.07   0.039     .0634307    2.416482
                  VT  |   1.109116   .6237803     1.78   0.075    -.1134708    2.331703
                  VA  |   1.115021   .7284197     1.53   0.126    -.3126552    2.542698
                  WA  |   .8379919   .6178159     1.36   0.175     -.372905    2.048889
                  WV  |   1.724945    .562394     3.07   0.002     .6226734    2.827217
                  WI  |   1.481474   .6022462     2.46   0.014     .3010932    2.661855
                  WY  |   2.438117   .6471564     3.77   0.000     1.169714     3.70652
                      |
                 year |
                1984  |   .0283209   .2268275     0.12   0.901    -.4162528    .4728946
                1988  |  -.3124437   .2286135    -1.37   0.172     -.760518    .1356306
                1994  |   .1935248     .24435     0.79   0.428    -.2853924     .672442
                1998  |  -.0039826   .2319538    -0.02   0.986    -.4586037    .4506385
                2004  |  -.3613056   .2529825    -1.43   0.153    -.8571422    .1345311
                2008  |   .0713475   .2686731     0.27   0.791    -.4552421    .5979371
----------------------+----------------------------------------------------------------
                /cut1 |  -1.585129   .7438016                     -3.042953   -.1273042
                /cut2 |   .6609475   .7373484                     -.7842287    2.106124
                /cut3 |   2.100934    .740963                       .648673    3.553195
---------------------------------------------------------------------------------------

. est sto d7

. ologit d_21a i.treated weekly_hours years_employ_state b3.pid5 agency_size log_agency_budget years_employ_a
> gency years_employ_position inst6017_nom i.state i.year [iweight=cem_weights] , r

Iteration 0:   log pseudolikelihood = -2483.4653  
Iteration 1:   log pseudolikelihood = -2374.8557  
Iteration 2:   log pseudolikelihood = -2373.9553  
Iteration 3:   log pseudolikelihood = -2373.9545  
Iteration 4:   log pseudolikelihood = -2373.9545  

Ordered logistic regression                     Number of obs     =      2,090
                                                Wald chi2(67)     =     126.70
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -2373.9545               Pseudo R2         =     0.0441

---------------------------------------------------------------------------------------
                      |               Robust
                d_21a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
----------------------+----------------------------------------------------------------
            1.treated |   .5602481   .2157496     2.60   0.009     .1373866    .9831097
         weekly_hours |   .0023255   .0079613     0.29   0.770    -.0132785    .0179294
   years_employ_state |   .0052245   .0096028     0.54   0.586    -.0135968    .0240457
                      |
                 pid5 |
          Republican  |   .0739078   .1949517     0.38   0.705    -.3081905    .4560061
     Lean Republican  |  -.1186671   .2882976    -0.41   0.681    -.6837199    .4463858
     Lean Democratic  |   .0405621   .2309456     0.18   0.861     -.412083    .4932072
          Democratic  |  -.1165418   .1829782    -0.64   0.524    -.4751725    .2420889
                      |
          agency_size |   -.084094   .0550602    -1.53   0.127      -.19201    .0238219
    log_agency_budget |   .0899738   .0402454     2.24   0.025     .0110943    .1688533
  years_employ_agency |   .0045448   .0102404     0.44   0.657     -.015526    .0246156
years_employ_position |   -.006914   .0141659    -0.49   0.625    -.0346788    .0208507
         inst6017_nom |     .01051    .007171     1.47   0.143    -.0035449    .0245649
                      |
                state |
                  AK  |   1.154396   .6847952     1.69   0.092    -.1877781     2.49657
                  AZ  |   1.123805   .6939503     1.62   0.105    -.2363127    2.483923
                  AR  |   .6316177   .7360115     0.86   0.391    -.8109383    2.074174
                  CA  |    1.85325   .6602698     2.81   0.005     .5591452    3.147355
                  CO  |   .7630294   .6931613     1.10   0.271    -.5955418    2.121601
                  CT  |    1.84468   .6916375     2.67   0.008     .4890955    3.200265
                  DE  |   .7606823   .6769498     1.12   0.261    -.5661149     2.08748
                  FL  |     1.2224   .6501047     1.88   0.060    -.0517815    2.496582
                  GA  |   1.049072   .6721426     1.56   0.119    -.2683035    2.366447
                  HI  |   .3699615   .7161065     0.52   0.605    -1.033581    1.773505
                  ID  |   1.540303   .7166414     2.15   0.032     .1357112    2.944894
                  IL  |   1.595265   1.019118     1.57   0.118    -.4021696      3.5927
                  IN  |    .789992   .6676557     1.18   0.237    -.5185891    2.098573
                  IA  |   1.742281    .656571     2.65   0.008     .4554257    3.029137
                  KS  |   1.982165   .7297606     2.72   0.007       .55186    3.412469
                  KY  |    2.20667   .8284653     2.66   0.008     .5829083    3.830433
                  LA  |   2.095896   .9124225     2.30   0.022     .3075806    3.884211
                  ME  |   1.107561    .907582     1.22   0.222    -.6712671    2.886389
                  MD  |   1.068918   .6602555     1.62   0.105    -.2251588    2.362995
                  MA  |    .225152   .6522235     0.35   0.730    -1.053183    1.503487
                  MI  |   1.093032   .7482958     1.46   0.144    -.3736005    2.559665
                  MN  |   .9530881    .697495     1.37   0.172    -.4139771    2.320153
                  MS  |    1.74371   .8028075     2.17   0.030     .1702368    3.317184
                  MO  |   1.116789   .6703846     1.67   0.096    -.1971408    2.430718
                  MT  |    1.38513   .9589951     1.44   0.149    -.4944655    3.264726
                  NE  |   1.025356   .7606206     1.35   0.178    -.4654333    2.516145
                  NV  |   1.377091   .6442467     2.14   0.033     .1143905    2.639791
                  NH  |   2.948722   .7047442     4.18   0.000     1.567449    4.329996
                  NJ  |   .8403414   .7454713     1.13   0.260    -.6207556    2.301438
                  NM  |   .0240868   .7301349     0.03   0.974    -1.406951    1.455125
                  NY  |   .5105057   .6644127     0.77   0.442    -.7917191    1.812731
                  NC  |   1.012955   .7152498     1.42   0.157    -.3889087    2.414819
                  ND  |    1.09435   .7648311     1.43   0.152    -.4046916    2.593391
                  OH  |    2.24757   .8451799     2.66   0.008     .5910476    3.904092
                  OK  |   1.943664    .689794     2.82   0.005     .5916927    3.295636
                  OR  |   .7536323   .6578189     1.15   0.252     -.535669    2.042934
                  PA  |   1.068098   .6770244     1.58   0.115     -.258845    2.395042
                  RI  |   .6655872   .6918089     0.96   0.336    -.6903332    2.021508
                  SC  |   1.895868    .756553     2.51   0.012     .4130512    3.378685
                  SD  |   1.205155   .6497789     1.85   0.064    -.0683885    2.478698
                  TN  |   1.754173   .7134914     2.46   0.014     .3557552     3.15259
                  TX  |    .372169   .6875649     0.54   0.588    -.9754334    1.719771
                  UT  |   1.277291   .6788285     1.88   0.060     -.053188    2.607771
                  VT  |   1.759205    .704758     2.50   0.013     .3779044    3.140505
                  VA  |   1.304885   .6736731     1.94   0.053    -.0154898     2.62526
                  WA  |   .4314069   .6853101     0.63   0.529    -.9117762     1.77459
                  WV  |   1.263602   .6894424     1.83   0.067    -.0876803    2.614884
                  WI  |   1.958291   .7151766     2.74   0.006     .5565706    3.360012
                  WY  |   1.567914   .7059073     2.22   0.026      .184361    2.951467
                      |
                 year |
                1984  |  -.3311665   .2234906    -1.48   0.138       -.7692     .106867
                1988  |  -.1803064   .2161544    -0.83   0.404    -.6039612    .2433484
                1994  |   -.077609   .2378409    -0.33   0.744    -.5437685    .3885505
                1998  |   .0698131   .2390183     0.29   0.770    -.3986541    .5382803
                2004  |  -.1892925    .250268    -0.76   0.449    -.6798088    .3012238
                2008  |   .1873746   .2633004     0.71   0.477    -.3286846    .7034338
----------------------+----------------------------------------------------------------
                /cut1 |   -.950636   .8654717                     -2.646929    .7456574
                /cut2 |   1.458095   .8419446                     -.1920859    3.108276
                /cut3 |   3.241112   .8449572                      1.585027    4.897198
---------------------------------------------------------------------------------------

. est sto d8

. 
.  esttab d1 d2 d3 d4 d5 d6 d7 d8 using Table_B5.rtf ,starlevels(+ 0.10 * 0.05 ** 0.01) cells(b(star fmt(3)) 
> se(par fmt(3))) ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Gov. Policy" "Legis. Policy" "Gov. Regs" "Legis. Regs" "Gov. Policy" "Legis. Policy" "Gov. Regs" 
> "Legis. Regs") 
(output written to Table_B5.rtf)

. 
. 
. clear all

. ***** RE-RUN PREAMBLE ***** 
. use par_asap.dta

. 
. gen intersection=0 if k_4a==1 & k_3a==1
(4,393 missing values generated)

. replace intersection=1 if k_4a==1 & k_3a==2
(1,306 real changes made)

. replace intersection=2 if  k_4a==0 & k_3a==1
(660 real changes made)

. replace intersection=3 if  k_4a==0 & k_3a==2
(188 real changes made)

. 
. label define mintersection 0"White Man"  1"White Woman" 2"Man of Color" 3"Woman of Color"

. 
. label value intersection mintersection

. 
. 
. rename a_2a civil_service 

. label var civil_service "Civil Servant"

. rename a_8a weekly_hours

. label var weekly_hours "Average Weekley Hours Worked"

. rename j_1a years_employ_state

. label var years_employ_state  "Years Employed in State Gov."

. rename j_1b years_employ_agency

. label var years_employ_agency  "Years Employed in Agency"

. rename j_1c years_employ_position 

. label var years_employ_position  "Years Employed in Position"

. gen age_2 = k_2a*k_2a
(490 missing values generated)

. label var age_2 "Age-squared"

. gen age = sqrt(age_2)
(490 missing values generated)

. label var age "Age"

. gen pid5= 1 if k_8b==2
(9,130 missing values generated)

. replace pid5= 2 if k_8b==4
(748 real changes made)

. replace pid5= 3 if k_8b==5
(1,210 real changes made)

. replace pid5= 4 if k_8b==3
(868 real changes made)

. replace pid5= 5 if k_8b==1
(3,880 real changes made)

. label var pid5 "Party ID"

. label define mpid5 1"Republican"  2"Lean Republican" 3"Independant" 4"Lean Democratic" 5"Democratic"

. 
. label value pid5 mpid5

. 
. 
. rename k_16a edu

. label var edu "Education"

. 
. rename a_3b agency_size

. label var agency_size "Total Agency Employees"

. 
. rename a_4b agency_budget 

. gen log_agency_budget = ln(1+agency_budget) 
(773 missing values generated)

. label var log_agency_budget "ln(Agency Budget, $2018)"

. 
. revrs e_1a 

. revrs e_1b 

. revrs e_1c 

. revrs e_1d 

. 
. label var reve_1a "Gov."

. label var reve_1b "Gov. Staff"

. label var reve_1c "Legis."

. label var reve_1d "Legis. Staff"

. 
. 
. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B6 ******
. ologit reve_1a i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r , vce(boot, reps(1000) seed(55803)) 
(running ologit on estimation sample)

Bootstrap replications (1000)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400
..................................................   450
..................................................   500
..................................................   550
..................................................   600
..................................................   650
..................................................   700
..................................................   750
..................................................   800
..................................................   850
..................................................   900
..................................................   950
..................................................  1000

Ordered logistic regression                     Number of obs     =      7,515
                                                Replications      =      1,000
                                                Wald chi2(93)     =    3136.17
                                                Prob > chi2       =     0.0000
Log likelihood = -8749.0873                     Pseudo R2         =     0.1552

----------------------------------------------------------------------------------------------------
                                   |   Observed   Bootstrap                         Normal-based
                           reve_1a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.2422217     .07123    -3.40   0.001      -.38183   -.1026134
                     Man of Color  |  -.1357595   .1013406    -1.34   0.180    -.3343835    .0628645
                   Woman of Color  |  -.5274129   .1658242    -3.18   0.001    -.8524225   -.2024034
                                   |
                     civil_service |
                              Yes  |   -.971733   .0612298   -15.87   0.000    -1.091741   -.8517248
                      weekly_hours |   .0521346   .0032401    16.09   0.000     .0457841    .0584852
                               age |  -.0374195    .022175    -1.69   0.092    -.0808818    .0060427
                             age_2 |     .00053   .0002186     2.42   0.015     .0001015    .0009584
                                   |
                               edu |
              High school or less  |   .0306371   .1943489     0.16   0.875    -.3502797    .4115539
                     Some college  |   .1162062    .109268     1.06   0.288    -.0979551    .3303674
                   Graduate study  |   .0538401    .075914     0.71   0.478    -.0949486    .2026287
                  Graduate degree  |  -.0971884   .0654647    -1.48   0.138    -.2254968    .0311199
                                   |
                years_employ_state |   -.000374   .0041889    -0.09   0.929     -.008584    .0078361
               years_employ_agency |  -.0313019   .0044356    -7.06   0.000    -.0399955   -.0226082
             years_employ_position |   .0076163   .0056485     1.35   0.178    -.0034546    .0186872
                                   |
                              pid5 |
                       Republican  |    .481098   .0849313     5.66   0.000     .3146358    .6475603
                  Lean Republican  |   .1207507   .1059311     1.14   0.254    -.0868703    .3283718
                  Lean Democratic  |  -.0231355   .0985142    -0.23   0.814    -.2162199    .1699489
                       Democratic  |    .473495   .0765206     6.19   0.000     .3235173    .6234727
                                   |
                       agency_size |
                           25-100  |   .1619845   .0746656     2.17   0.030     .0156426    .3083264
                          101-500  |   .5105166   .0855592     5.97   0.000     .3428236    .6782096
                        501-1,000  |   .7649114    .115461     6.62   0.000      .538612    .9912108
                      1,001-5,000  |   1.068553   .1177174     9.08   0.000     .8378313    1.299275
                       Over 5,000  |   1.494491   .1658394     9.01   0.000     1.169452     1.81953
                                   |
                 log_agency_budget |   .1757835   .0204349     8.60   0.000     .1357319    .2158351
                      inst6017_nom |  -.0030011   .0029487    -1.02   0.309    -.0087805    .0027784
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .6925461   .1701109     4.07   0.000     .3591349    1.025957
                Staff: Non-Fiscal  |  -.2202206   .1579463    -1.39   0.163    -.5297897    .0893485
Income Security & Social Services  |   -1.47653    .141905   -10.41   0.000    -1.754659   -1.198402
                        Education  |  -.9776317   .1540809    -6.34   0.000    -1.279625   -.6756387
                           Health  |  -1.648944   .1508091   -10.93   0.000    -1.944524   -1.353364
                Natural Resources  |  -.7923242   .1332091    -5.95   0.000    -1.053409   -.5312392
             Environment & Energy  |  -.7873803   .1405704    -5.60   0.000    -1.062893   -.5118673
             Economic Development  |   .0223083   .1411273     0.16   0.874    -.2542961    .2989128
                 Criminal Justice  |  -.9552778   .1376427    -6.94   0.000    -1.225053   -.6855032
                       Regulatory  |  -1.257715   .1384874    -9.08   0.000    -1.529146   -.9862851
                   Transportation  |    -1.0062   .1522485    -6.61   0.000    -1.304602   -.7077988
                            Other  |   -.757503   .1441155    -5.26   0.000    -1.039964   -.4750417
                                   |
                             state |
                               AK  |  -.3341416   .2245318    -1.49   0.137    -.7742159    .1059326
                               AZ  |  -1.072071   .2470107    -4.34   0.000    -1.556203   -.5879391
                               AR  |  -.2319074   .2044619    -1.13   0.257    -.6326454    .1688307
                               CA  |  -2.499601    .253011    -9.88   0.000    -2.995493   -2.003709
                               CO  |  -.0331212   .2112129    -0.16   0.875    -.4470908    .3808484
                               CT  |  -1.157115   .2588727    -4.47   0.000    -1.664496   -.6497336
                               DE  |   -.367357   .2088691    -1.76   0.079    -.7767329    .0420188
                               FL  |  -1.685318   .2521476    -6.68   0.000    -2.179518   -1.191118
                               GA  |  -.9216965   .2307288    -3.99   0.000    -1.373917   -.4694763
                               HI  |  -.7774421   .2489755    -3.12   0.002    -1.265425   -.2894591
                               ID  |   .2447971    .208478     1.17   0.240    -.1638123    .6534066
                               IL  |  -1.432487   .2560109    -5.60   0.000    -1.934259   -.9307151
                               IN  |  -.5692946   .2289987    -2.49   0.013    -1.018124   -.1204654
                               IA  |  -.2820726   .2015167    -1.40   0.162    -.6770381    .1128929
                               KS  |  -.4032152   .2284498    -1.77   0.078    -.8509687    .0445383
                               KY  |  -1.063754   .2251899    -4.72   0.000    -1.505118   -.6223899
                               LA  |  -.8155946    .266706    -3.06   0.002    -1.338329   -.2928604
                               ME  |  -.0783662   .2301433    -0.34   0.733    -.5294388    .3727063
                               MD  |  -.9876069   .2427713    -4.07   0.000     -1.46343   -.5117839
                               MA  |  -1.693045   .2460973    -6.88   0.000    -2.175387   -1.210703
                               MI  |   -.874717   .2218899    -3.94   0.000    -1.309613   -.4398207
                               MN  |  -1.107307   .2258646    -4.90   0.000    -1.549994   -.6646207
                               MS  |  -.2822958   .2309795    -1.22   0.222    -.7350072    .1704157
                               MO  |  -1.220202   .2132855    -5.72   0.000    -1.638234   -.8021697
                               MT  |   .1358397   .2033773     0.67   0.504    -.2627725    .5344519
                               NE  |   .1869023   .2362522     0.79   0.429    -.2761436    .6499481
                               NV  |  -.2360691   .2202498    -1.07   0.284    -.6677508    .1956127
                               NH  |  -.0685534   .2242187    -0.31   0.760     -.508014    .3709072
                               NJ  |  -1.228063    .242806    -5.06   0.000    -1.703954   -.7521721
                               NM  |   .0465281   .2309215     0.20   0.840    -.4060698     .499126
                               NY  |  -2.188579   .2691061    -8.13   0.000    -2.716018   -1.661141
                               NC  |  -1.032744    .199786    -5.17   0.000    -1.424317   -.6411703
                               ND  |   .6604772   .2091512     3.16   0.002     .2505484    1.070406
                               OH  |  -1.235707    .235258    -5.25   0.000    -1.696804   -.7746093
                               OK  |  -.6671675   .2129208    -3.13   0.002    -1.084485   -.2498503
                               OR  |  -.2735063   .2207682    -1.24   0.215     -.706204    .1591914
                               PA  |  -1.880874   .2266844    -8.30   0.000    -2.325167   -1.436581
                               RI  |   .2145086   .2349645     0.91   0.361    -.2460133    .6750304
                               SC  |  -.5503567    .214796    -2.56   0.010     -.971349   -.1293643
                               SD  |   .3450091   .2156413     1.60   0.110    -.0776401    .7676582
                               TN  |  -1.180326   .2322718    -5.08   0.000     -1.63557   -.7250816
                               TX  |  -1.979577   .2191978    -9.03   0.000    -2.409197   -1.549957
                               UT  |   .0487906   .1959989     0.25   0.803    -.3353602    .4329414
                               VT  |    .260382   .2151237     1.21   0.226    -.1612528    .6820167
                               VA  |  -1.115041   .2286516    -4.88   0.000     -1.56319   -.6668922
                               WA  |  -.9946893   .2435374    -4.08   0.000    -1.472014   -.5173648
                               WV  |  -.5057771   .2208361    -2.29   0.022    -.9386079   -.0729464
                               WI  |  -.4418259   .2165793    -2.04   0.041    -.8663136   -.0173383
                               WY  |   .5443989   .1904186     2.86   0.004     .1711852    .9176125
                                   |
                              year |
                             1978  |  -.6629782   .0907497    -7.31   0.000    -.8408444    -.485112
                             1984  |   -.673541   .0864686    -7.79   0.000    -.8430164   -.5040656
                             1988  |  -.9775924    .080419   -12.16   0.000    -1.135211    -.819974
                             1994  |  -.8358436   .0833136   -10.03   0.000    -.9991353   -.6725519
                             1998  |  -1.171177   .0942067   -12.43   0.000    -1.355819   -.9865355
                             2004  |  -1.224451   .0974448   -12.57   0.000    -1.415439   -1.033462
                             2008  |  -1.507369   .1231669   -12.24   0.000    -1.748772   -1.265966
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.505395   .6301275                     -2.740422   -.2703675
                             /cut2 |   1.137216   .6295186                     -.0966175     2.37105
                             /cut3 |   2.614267    .632062                      1.375448    3.853086
                             /cut4 |   5.130007   .6388952                      3.877795    6.382219
----------------------------------------------------------------------------------------------------

. est sto boot_m1

. 
. ologit reve_1b i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r , vce(boot, reps(1000) seed(55803)) 
(running ologit on estimation sample)

Bootstrap replications (1000)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400
..................................................   450
..................................................   500
..................................................   550
..................................................   600
..................................................   650
..................................................   700
..................................................   750
..................................................   800
..................................................   850
..................................................   900
..................................................   950
..................................................  1000

Ordered logistic regression                     Number of obs     =      6,378
                                                Replications      =      1,000
                                                Wald chi2(92)     =    2219.69
                                                Prob > chi2       =     0.0000
Log likelihood = -8073.6594                     Pseudo R2         =     0.1229

----------------------------------------------------------------------------------------------------
                                   |   Observed   Bootstrap                         Normal-based
                           reve_1b |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.1502099   .0696715    -2.16   0.031    -.2867635   -.0136564
                     Man of Color  |  -.0567718   .1029118    -0.55   0.581    -.2584752    .1449316
                   Woman of Color  |  -.5224028   .1715652    -3.04   0.002    -.8586643   -.1861413
                                   |
                     civil_service |
                              Yes  |  -.8010587   .0608556   -13.16   0.000    -.9203334    -.681784
                      weekly_hours |   .0479222   .0034613    13.84   0.000     .0411381    .0547064
                               age |  -.0767768   .0239205    -3.21   0.001    -.1236601   -.0298936
                             age_2 |   .0007002    .000238     2.94   0.003     .0002338    .0011666
                                   |
                               edu |
              High school or less  |   .2658405   .2333207     1.14   0.255    -.1914597    .7231408
                     Some college  |   .1530398    .122378     1.25   0.211    -.0868168    .3928963
                   Graduate study  |   .1476438   .0853697     1.73   0.084    -.0196777    .3149653
                  Graduate degree  |   .0734268   .0687065     1.07   0.285    -.0612355    .2080891
                                   |
                years_employ_state |   .0056667   .0043611     1.30   0.194    -.0028809    .0142143
               years_employ_agency |  -.0282912    .004662    -6.07   0.000    -.0374285    -.019154
             years_employ_position |  -.0066664   .0060888    -1.09   0.274    -.0186003    .0052674
                                   |
                              pid5 |
                       Republican  |   .3837354   .0913764     4.20   0.000     .2046409    .5628299
                  Lean Republican  |   .0228367   .1100604     0.21   0.836    -.1928777    .2385511
                  Lean Democratic  |  -.0635507   .1055421    -0.60   0.547    -.2704095    .1433081
                       Democratic  |   .3259516   .0835796     3.90   0.000     .1621386    .4897647
                                   |
                       agency_size |
                           25-100  |  -.0445093   .0785874    -0.57   0.571    -.1985378    .1095193
                          101-500  |   .1968848   .0900236     2.19   0.029     .0204419    .3733277
                        501-1,000  |   .3376189   .1186488     2.85   0.004     .1050715    .5701663
                      1,001-5,000  |   .6280194   .1310393     4.79   0.000     .3711871    .8848517
                       Over 5,000  |   1.022571   .1814965     5.63   0.000     .6668444    1.378298
                                   |
                 log_agency_budget |   .1899252   .0218153     8.71   0.000     .1471679    .2326825
                      inst6017_nom |   .0028871   .0033154     0.87   0.384    -.0036109    .0093851
                                   |
                          funcat13 |
                    Staff: Fiscal  |   1.405647    .181176     7.76   0.000     1.050548    1.760745
                Staff: Non-Fiscal  |   .9466027    .184053     5.14   0.000     .5858655     1.30734
Income Security & Social Services  |  -.4537725   .1535265    -2.96   0.003    -.7546788   -.1528661
                        Education  |  -.4254235   .1621393    -2.62   0.009    -.7432108   -.1076363
                           Health  |  -.6096505   .1546331    -3.94   0.000    -.9127259   -.3065752
                Natural Resources  |  -.0851974   .1417583    -0.60   0.548    -.3630386    .1926438
             Environment & Energy  |   .0260771   .1518427     0.17   0.864    -.2715291    .3236833
             Economic Development  |   .7596595   .1499266     5.07   0.000     .4658087     1.05351
                 Criminal Justice  |   .0158167   .1544773     0.10   0.918    -.2869532    .3185867
                       Regulatory  |  -.6198936   .1355089    -4.57   0.000    -.8854862   -.3543011
                   Transportation  |  -.2217456   .1573824    -1.41   0.159    -.5302095    .0867182
                            Other  |   .1386793   .1446458     0.96   0.338    -.1448213    .4221798
                                   |
                             state |
                               AK  |  -.0763772   .2323006    -0.33   0.742    -.5316779    .3789236
                               AZ  |  -.3752213   .2462285    -1.52   0.128    -.8578202    .1073776
                               AR  |   .3394096   .2267146     1.50   0.134     -.104943    .7837621
                               CA  |  -1.533002   .2618943    -5.85   0.000    -2.046305   -1.019699
                               CO  |  -.2716633   .2258733    -1.20   0.229    -.7143669    .1710403
                               CT  |  -.8201582    .279821    -2.93   0.003    -1.368597   -.2717191
                               DE  |   -.853052   .2293917    -3.72   0.000    -1.302652   -.4034525
                               FL  |  -1.320788   .2465211    -5.36   0.000     -1.80396   -.8376151
                               GA  |  -.8142959   .2608559    -3.12   0.002    -1.325564   -.3030278
                               HI  |  -1.396295   .2803055    -4.98   0.000    -1.945684    -.846906
                               ID  |    .726494   .2333552     3.11   0.002     .2691263    1.183862
                               IL  |  -.3944151   .2960455    -1.33   0.183    -.9746535    .1858234
                               IN  |   .1277181   .2460148     0.52   0.604    -.3544621    .6098982
                               IA  |  -.3074279   .2267357    -1.36   0.175    -.7518216    .1369659
                               KS  |  -.5489781   .2291055    -2.40   0.017    -.9980166   -.0999396
                               KY  |  -.8118887   .2438218    -3.33   0.001    -1.289771   -.3340068
                               LA  |  -.3434393    .251124    -1.37   0.171    -.8356334    .1487548
                               ME  |   .1849485   .2452644     0.75   0.451    -.2957609    .6656579
                               MD  |  -.4369056   .2372518    -1.84   0.066    -.9019105    .0280993
                               MA  |  -1.065537   .2759192    -3.86   0.000    -1.606329   -.5247454
                               MI  |  -.3496174   .2446944    -1.43   0.153    -.8292095    .1299748
                               MN  |  -.9795967   .2300103    -4.26   0.000    -1.430409   -.5287847
                               MS  |  -.5658047   .2597597    -2.18   0.029    -1.074924    -.056685
                               MO  |  -1.091504   .2351496    -4.64   0.000    -1.552389   -.6306194
                               MT  |   .1691514   .2138746     0.79   0.429    -.2500352     .588338
                               NE  |  -.2307015   .2339502    -0.99   0.324    -.6892354    .2278325
                               NV  |  -.2566648   .2282913    -1.12   0.261    -.7041077     .190778
                               NH  |   .0673188   .2455676     0.27   0.784    -.4139848    .5486225
                               NJ  |   -.835969   .2619252    -3.19   0.001    -1.349333    -.322605
                               NM  |  -.2578871   .2434853    -1.06   0.290    -.7351095    .2193353
                               NY  |  -.2012437   .2993765    -0.67   0.501    -.7880107    .3855234
                               NC  |  -.9560659   .2240179    -4.27   0.000    -1.395133   -.5169988
                               ND  |   .2226899   .2118757     1.05   0.293    -.1925787    .6379586
                               OH  |  -.9561178   .2491708    -3.84   0.000    -1.444483    -.467752
                               OK  |  -.7989965   .2332996    -3.42   0.001    -1.256255   -.3417376
                               OR  |  -.3182658   .2335823    -1.36   0.173    -.7760787    .1395471
                               PA  |  -1.466266   .2569733    -5.71   0.000    -1.969924   -.9626071
                               RI  |   .3960384   .2480005     1.60   0.110    -.0900336    .8821104
                               SC  |   -.434628   .2333143    -1.86   0.062    -.8919157    .0226596
                               SD  |    .076803   .2344531     0.33   0.743    -.3827168    .5363227
                               TN  |  -1.131338   .2407013    -4.70   0.000    -1.603104   -.6595722
                               TX  |  -1.245401   .2325129    -5.36   0.000    -1.701118   -.7896838
                               UT  |  -.3692784   .2156189    -1.71   0.087    -.7918837    .0533268
                               VT  |  -.0581917   .2380997    -0.24   0.807    -.5248585    .4084752
                               VA  |  -.7031821   .2781733    -2.53   0.011    -1.248392   -.1579724
                               WA  |  -.9891452   .2275279    -4.35   0.000    -1.435092   -.5431988
                               WV  |  -.4904082   .2710601    -1.81   0.070    -1.021676    .0408599
                               WI  |  -.5345467   .2311258    -2.31   0.021     -.987545   -.0815484
                               WY  |   .1794183   .2138403     0.84   0.401     -.239701    .5985375
                                   |
                              year |
                             1984  |   .0662276   .0921349     0.72   0.472    -.1143535    .2468087
                             1988  |   .1299014   .0881814     1.47   0.141     -.042931    .3027337
                             1994  |    .022564   .0949004     0.24   0.812    -.1634373    .2085653
                             1998  |  -.1963388   .1004783    -1.95   0.051    -.3932726     .000595
                             2004  |  -.2686975   .1048726    -2.56   0.010     -.474244   -.0631509
                             2008  |  -.2719732   .1238285    -2.20   0.028    -.5146726   -.0292739
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -3.539681   .6656151                     -4.844262   -2.235099
                             /cut2 |  -.5321222   .6522813                      -1.81057    .7463256
                             /cut3 |   .7528796   .6522116                     -.5254315    2.031191
                             /cut4 |   2.759331   .6534284                      1.478635    4.040027
----------------------------------------------------------------------------------------------------

. est sto boot_m2

. 
. ologit reve_1c i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r , vce(boot, reps(1000) seed(55803)) 
(running ologit on estimation sample)

Bootstrap replications (1000)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400
..................................................   450
..................................................   500
..................................................   550
..................................................   600
..................................................   650
..................................................   700
..................................................   750
..................................................   800
..................................................   850
..................................................   900
..................................................   950
..................................................  1000

Ordered logistic regression                     Number of obs     =      7,543
                                                Replications      =      1,000
                                                Wald chi2(93)     =    1933.28
                                                Prob > chi2       =     0.0000
Log likelihood = -9360.5601                     Pseudo R2         =     0.0958

----------------------------------------------------------------------------------------------------
                                   |   Observed   Bootstrap                         Normal-based
                           reve_1c |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.1532275   .0691394    -2.22   0.027    -.2887382   -.0177168
                     Man of Color  |  -.5317392   .1007622    -5.28   0.000    -.7292295    -.334249
                   Woman of Color  |  -.6349348    .185986    -3.41   0.001    -.9994606   -.2704089
                                   |
                     civil_service |
                              Yes  |  -.4786386   .0578058    -8.28   0.000    -.5919359   -.3653413
                      weekly_hours |   .0395543   .0030255    13.07   0.000     .0336245    .0454841
                               age |  -.0155138   .0231027    -0.67   0.502    -.0607943    .0297668
                             age_2 |   6.43e-06   .0002308     0.03   0.978    -.0004458    .0004587
                                   |
                               edu |
              High school or less  |   .0429885   .2139051     0.20   0.841    -.3762578    .4622348
                     Some college  |  -.1672944   .1048822    -1.60   0.111    -.3728598     .038271
                   Graduate study  |   .1129532   .0775245     1.46   0.145    -.0389921    .2648985
                  Graduate degree  |   .0497169   .0614252     0.81   0.418    -.0706742    .1701081
                                   |
                years_employ_state |   .0049376   .0038539     1.28   0.200    -.0026158     .012491
               years_employ_agency |  -.0098846   .0042165    -2.34   0.019    -.0181487   -.0016205
             years_employ_position |   .0077178   .0054329     1.42   0.155    -.0029304     .018366
                                   |
                              pid5 |
                       Republican  |   .2280009    .078331     2.91   0.004      .074475    .3815267
                  Lean Republican  |  -.0335429   .1016512    -0.33   0.741    -.2327756    .1656898
                  Lean Democratic  |   -.002536   .0926138    -0.03   0.978    -.1840557    .1789836
                       Democratic  |   .1816716   .0733109     2.48   0.013     .0379848    .3253584
                                   |
                       agency_size |
                           25-100  |   .2577081   .0706772     3.65   0.000     .1191834    .3962328
                          101-500  |   .4706283   .0811369     5.80   0.000     .3116029    .6296536
                        501-1,000  |   .5575088   .1086723     5.13   0.000      .344515    .7705026
                      1,001-5,000  |   .6310467     .11585     5.45   0.000     .4039849    .8581085
                       Over 5,000  |   .8554307    .154544     5.54   0.000       .55253    1.158331
                                   |
                 log_agency_budget |   .1545551   .0193863     7.97   0.000     .1165586    .1925515
                      inst6017_nom |   .0036019   .0026029     1.38   0.166    -.0014998    .0087035
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.7217645   .1508668    -4.78   0.000    -1.017458   -.4260711
                Staff: Non-Fiscal  |  -1.344385   .1401681    -9.59   0.000     -1.61911   -1.069661
Income Security & Social Services  |  -1.544121   .1288616   -11.98   0.000    -1.796685   -1.291557
                        Education  |  -1.333907   .1359784    -9.81   0.000     -1.60042   -1.067394
                           Health  |  -1.444351    .131248   -11.00   0.000    -1.701593    -1.18711
                Natural Resources  |  -.9783398   .1240068    -7.89   0.000    -1.221389    -.735291
             Environment & Energy  |  -1.157852   .1277469    -9.06   0.000    -1.408231   -.9074724
             Economic Development  |  -1.169661   .1285013    -9.10   0.000    -1.421519   -.9178033
                 Criminal Justice  |  -1.490325   .1291434   -11.54   0.000    -1.743441   -1.237208
                       Regulatory  |  -1.341997   .1207639   -11.11   0.000     -1.57869   -1.105304
                   Transportation  |   -.921331   .1465121    -6.29   0.000    -1.208489   -.6341726
                            Other  |  -1.484794   .1341544   -11.07   0.000    -1.747731   -1.221856
                                   |
                             state |
                               AK  |   .1844862   .2272767     0.81   0.417    -.2609678    .6299403
                               AZ  |   .0686257   .2510544     0.27   0.785    -.4234319    .5606832
                               AR  |   .5962324   .2382825     2.50   0.012     .1292072    1.063258
                               CA  |  -.0899827   .2547906    -0.35   0.724    -.5893631    .4093978
                               CO  |   .3909344   .2199854     1.78   0.076    -.0402291    .8220979
                               CT  |   .1792289   .2495812     0.72   0.473    -.3099412     .668399
                               DE  |   .1713338   .2233595     0.77   0.443    -.2664429    .6091104
                               FL  |  -.5273958   .2347346    -2.25   0.025    -.9874671   -.0673245
                               GA  |   .3733606   .2394236     1.56   0.119    -.0959011    .8426223
                               HI  |  -.4723271    .271208    -1.74   0.082    -1.003885    .0592308
                               ID  |  -.0087548   .2358691    -0.04   0.970    -.4710497    .4535401
                               IL  |   .1443683   .2515506     0.57   0.566    -.3486619    .6373984
                               IN  |  -.2772225   .2309786    -1.20   0.230    -.7299321    .1754872
                               IA  |  -.0552067   .2111763    -0.26   0.794    -.4691046    .3586912
                               KS  |   .5429078   .2329769     2.33   0.020     .0862815    .9995342
                               KY  |   -.493915    .251405    -1.96   0.049    -.9866598   -.0011702
                               LA  |   .6365047   .2707021     2.35   0.019     .1059383    1.167071
                               ME  |   .8528493   .2350275     3.63   0.000     .3922039    1.313495
                               MD  |   .2340007   .2163775     1.08   0.279    -.1900913    .6580928
                               MA  |    .473201    .260603     1.82   0.069    -.0375715    .9839734
                               MI  |   .8221413   .2385958     3.45   0.001     .3545021    1.289781
                               MN  |   .3196358   .2136005     1.50   0.135    -.0990135     .738285
                               MS  |   .3302594   .2471592     1.34   0.181    -.1541638    .8146826
                               MO  |   .3331271   .2254565     1.48   0.140    -.1087595    .7750137
                               MT  |  -.2830532   .2228598    -1.27   0.204    -.7198504     .153744
                               NE  |  -.0741863   .2237368    -0.33   0.740    -.5127023    .3643297
                               NV  |  -.7577281   .2143767    -3.53   0.000    -1.177899   -.3375574
                               NH  |   1.064797   .2239124     4.76   0.000     .6259368    1.503657
                               NJ  |  -.4378222   .2383426    -1.84   0.066     -.904965    .0293206
                               NM  |  -.4457853   .2296674    -1.94   0.052    -.8959253    .0043546
                               NY  |  -.5236403   .2853262    -1.84   0.066    -1.082869    .0355887
                               NC  |  -.1303479   .2056836    -0.63   0.526    -.5334803    .2727845
                               ND  |  -.3949463   .2117126    -1.87   0.062    -.8098954    .0200028
                               OH  |  -.3798706   .2227635    -1.71   0.088    -.8164791    .0567378
                               OK  |    .767976   .2337444     3.29   0.001     .3098455    1.226107
                               OR  |  -.2785938   .2124871    -1.31   0.190    -.6950609    .1378732
                               PA  |   .1065086   .2478809     0.43   0.667    -.3793291    .5923462
                               RI  |  -.0517783   .2557731    -0.20   0.840    -.5530843    .4495277
                               SC  |   1.077082   .2504397     4.30   0.000     .5862293    1.567935
                               SD  |  -.8420329   .2293231    -3.67   0.000    -1.291498   -.3925679
                               TN  |   .0646205   .2388668     0.27   0.787    -.4035499    .5327908
                               TX  |  -.0094745   .2454492    -0.04   0.969    -.4905462    .4715972
                               UT  |  -.5591416   .2111482    -2.65   0.008    -.9729845   -.1452987
                               VT  |   .7496343   .2382358     3.15   0.002     .2827008    1.216568
                               VA  |  -.3137102   .2372922    -1.32   0.186    -.7787945     .151374
                               WA  |  -.4032374   .2131957    -1.89   0.059    -.8210933    .0146184
                               WV  |  -.3648495   .2328289    -1.57   0.117    -.8211857    .0914867
                               WI  |   .2197584   .2120596     1.04   0.300    -.1958707    .6353875
                               WY  |  -.7727914   .2210496    -3.50   0.000    -1.206041   -.3395421
                                   |
                              year |
                             1978  |  -.5116036   .0912597    -5.61   0.000    -.6904693   -.3327379
                             1984  |   -.507846   .0905849    -5.61   0.000    -.6853891   -.3303029
                             1988  |  -.4688999   .0850359    -5.51   0.000    -.6355672   -.3022325
                             1994  |   -.466606    .093888    -4.97   0.000    -.6506231   -.2825889
                             1998  |  -.7226027   .0911078    -7.93   0.000    -.9011708   -.5440347
                             2004  |  -.9583222    .096224    -9.96   0.000    -1.146918   -.7697266
                             2008  |   -.933202   .1131349    -8.25   0.000    -1.154942   -.7114616
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -4.174863   .6415312                     -5.432241   -2.917485
                             /cut2 |  -.4940411   .6361384                      -1.74085    .7527672
                             /cut3 |   .9883115   .6367818                     -.2597578    2.236381
                             /cut4 |   3.141685   .6383846                      1.890474    4.392896
----------------------------------------------------------------------------------------------------

. est sto boot_m3

. 
. ologit reve_1d i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r , vce(boot, reps(1000) seed(55803)) 
(running ologit on estimation sample)

Bootstrap replications (1000)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400
..................................................   450
..................................................   500
..................................................   550
..................................................   600
..................................................   650
..................................................   700
..................................................   750
..................................................   800
..................................................   850
..................................................   900
..................................................   950
..................................................  1000

Ordered logistic regression                     Number of obs     =      6,340
                                                Replications      =      1,000
                                                Wald chi2(92)     =    1066.47
                                                Prob > chi2       =     0.0000
Log likelihood = -8194.7467                     Pseudo R2         =     0.0611

----------------------------------------------------------------------------------------------------
                                   |   Observed   Bootstrap                         Normal-based
                           reve_1d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.0915631   .0723435    -1.27   0.206    -.2333537    .0502275
                     Man of Color  |  -.2571474    .101167    -2.54   0.011     -.455431   -.0588637
                   Woman of Color  |  -.6066361   .2109235    -2.88   0.004    -1.020039   -.1932337
                                   |
                     civil_service |
                              Yes  |  -.2674122   .0607926    -4.40   0.000    -.3865635   -.1482609
                      weekly_hours |   .0295276    .003124     9.45   0.000     .0234047    .0356504
                               age |  -.0403184   .0269035    -1.50   0.134    -.0930483    .0124116
                             age_2 |   .0002548   .0002701     0.94   0.346    -.0002746    .0007842
                                   |
                               edu |
              High school or less  |   .0765339   .2681245     0.29   0.775    -.4489805    .6020483
                     Some college  |  -.0604091   .1221447    -0.49   0.621    -.2998084    .1789901
                   Graduate study  |   .1352846   .0845492     1.60   0.110    -.0304287     .300998
                  Graduate degree  |   .0574484   .0658387     0.87   0.383    -.0715932      .18649
                                   |
                years_employ_state |   .0120718   .0041333     2.92   0.003     .0039707     .020173
               years_employ_agency |  -.0078704   .0044486    -1.77   0.077    -.0165895    .0008486
             years_employ_position |    .004455   .0058369     0.76   0.445     -.006985    .0158951
                                   |
                              pid5 |
                       Republican  |   .0864186   .0828862     1.04   0.297    -.0760353    .2488725
                  Lean Republican  |   .0044505   .1094905     0.04   0.968     -.210147    .2190479
                  Lean Democratic  |  -.0091306   .1061258    -0.09   0.931    -.2171334    .1988722
                       Democratic  |   .0612516   .0767968     0.80   0.425    -.0892674    .2117706
                                   |
                       agency_size |
                           25-100  |   .0577822   .0767557     0.75   0.452    -.0926563    .2082206
                          101-500  |   .0949199   .0846396     1.12   0.262    -.0709707    .2608104
                        501-1,000  |   .1025891    .114975     0.89   0.372    -.1227578    .3279359
                      1,001-5,000  |  -.0089695    .126524    -0.07   0.943     -.256952    .2390129
                       Over 5,000  |   .2036781   .1643513     1.24   0.215    -.1184445    .5258008
                                   |
                 log_agency_budget |   .0999747   .0206605     4.84   0.000     .0594808    .1404686
                      inst6017_nom |   .0060982   .0029587     2.06   0.039     .0002992    .0118972
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.1229972   .1621083    -0.76   0.448    -.4407236    .1947293
                Staff: Non-Fiscal  |  -.8768568   .1640628    -5.34   0.000    -1.198414   -.5552995
Income Security & Social Services  |  -.9503731    .155056    -6.13   0.000    -1.254277   -.6464689
                        Education  |  -.6935631   .1609847    -4.31   0.000    -1.009087   -.3780389
                           Health  |  -.9182932   .1622908    -5.66   0.000    -1.236377   -.6002091
                Natural Resources  |  -.9120763   .1472642    -6.19   0.000    -1.200709   -.6234438
             Environment & Energy  |  -1.032433   .1481787    -6.97   0.000    -1.322858   -.7420084
             Economic Development  |  -1.134385   .1482833    -7.65   0.000    -1.425015   -.8437547
                 Criminal Justice  |  -.9563278   .1543947    -6.19   0.000    -1.258936   -.6537198
                       Regulatory  |  -1.162944   .1413121    -8.23   0.000    -1.439911   -.8859773
                   Transportation  |  -.8374815   .1686754    -4.97   0.000    -1.168079   -.5068838
                            Other  |  -.9052627   .1568418    -5.77   0.000    -1.212667   -.5978584
                                   |
                             state |
                               AK  |   1.399893   .2520636     5.55   0.000     .9058574    1.893929
                               AZ  |   .9238635   .2606282     3.54   0.000     .4130416    1.434685
                               AR  |   .7222201   .2684272     2.69   0.007     .1961124    1.248328
                               CA  |   1.040541   .2883324     3.61   0.000     .4754196    1.605662
                               CO  |   .7062144   .2499618     2.83   0.005     .2162983    1.196131
                               CT  |     .54922   .2812172     1.95   0.051    -.0019555    1.100396
                               DE  |   .0967001   .2752877     0.35   0.725    -.4428539    .6362541
                               FL  |    .917924   .2719058     3.38   0.001     .3849983     1.45085
                               GA  |   .4995448   .2746253     1.82   0.069     -.038711    1.037801
                               HI  |   -.098179   .2990151    -0.33   0.743    -.6842378    .4878798
                               ID  |   .5452425   .2485646     2.19   0.028     .0580649     1.03242
                               IL  |   .5357001   .2784297     1.92   0.054    -.0100121    1.081412
                               IN  |   .1926003   .2651094     0.73   0.468    -.3270045    .7122051
                               IA  |   .4623393   .2389241     1.94   0.053    -.0059434    .9306219
                               KS  |   1.192527     .25408     4.69   0.000     .6945393    1.690515
                               KY  |   .6270707   .2748365     2.28   0.023     .0884011     1.16574
                               LA  |   .8133197   .2980575     2.73   0.006     .2291377    1.397502
                               ME  |   .8874817   .2838852     3.13   0.002     .3310768    1.443886
                               MD  |   .8027602   .2657751     3.02   0.003     .2818506     1.32367
                               MA  |   .8799829   .2961575     2.97   0.003     .2995248    1.460441
                               MI  |   1.697745   .2676979     6.34   0.000     1.173067    2.222424
                               MN  |   1.185779    .253685     4.67   0.000     .6885657    1.682993
                               MS  |   .4389355   .2689252     1.63   0.103    -.0881481    .9660191
                               MO  |   .7516882   .2545985     2.95   0.003     .2526843    1.250692
                               MT  |   .4021156   .2442259     1.65   0.100    -.0765583    .8807896
                               NE  |   .9359898   .2556393     3.66   0.000      .434946    1.437034
                               NV  |   .4210234   .2424799     1.74   0.083    -.0542285    .8962752
                               NH  |    .861979   .2756365     3.13   0.002     .3217414    1.402217
                               NJ  |   .3240292   .2678318     1.21   0.226    -.2009115    .8489699
                               NM  |    .450611   .2785307     1.62   0.106    -.0952991    .9965212
                               NY  |   .3916939   .3571131     1.10   0.273    -.3082349    1.091623
                               NC  |   .3156418   .2452117     1.29   0.198    -.1649642    .7962478
                               ND  |  -.6404053   .2593782    -2.47   0.014    -1.148777   -.1320334
                               OH  |   .5187461   .2761453     1.88   0.060    -.0224888    1.059981
                               OK  |   1.100864    .251875     4.37   0.000     .6071979     1.59453
                               OR  |   .6240373   .2594175     2.41   0.016     .1155883    1.132486
                               PA  |   1.029567   .2795606     3.68   0.000     .4816385    1.577496
                               RI  |  -.2562584   .2887373    -0.89   0.375    -.8221731    .3096564
                               SC  |   1.400709   .2768855     5.06   0.000      .858023    1.943394
                               SD  |  -.2997918   .2626687    -1.14   0.254    -.8146131    .2150294
                               TN  |   .5386902    .266091     2.02   0.043     .0171614    1.060219
                               TX  |   1.567741   .2622897     5.98   0.000     1.053662    2.081819
                               UT  |   .5426185   .2449821     2.21   0.027     .0624624    1.022775
                               VT  |   .2893295   .2791352     1.04   0.300    -.2577655    .8364245
                               VA  |   .3164445   .2656434     1.19   0.234     -.204207     .837096
                               WA  |   .6177409   .2458095     2.51   0.012     .1359632    1.099519
                               WV  |   .1170794   .2667039     0.44   0.661    -.4056505    .6398094
                               WI  |   1.243647    .253894     4.90   0.000     .7460236     1.74127
                               WY  |  -.2981704   .2493179    -1.20   0.232    -.7868244    .1904836
                                   |
                              year |
                             1984  |  -.0881298    .087036    -1.01   0.311    -.2587173    .0824576
                             1988  |    .154664   .0871358     1.77   0.076    -.0161191     .325447
                             1994  |   .2173252   .0941311     2.31   0.021     .0328317    .4018187
                             1998  |  -.0626998   .1017234    -0.62   0.538     -.262074    .1366744
                             2004  |  -.4073416   .0980627    -4.15   0.000    -.5995409   -.2151422
                             2008  |  -.1814891   .1103254    -1.65   0.100    -.3977228    .0347447
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -3.267728   .7161564                     -4.671369   -1.864087
                             /cut2 |  -.2093042   .7139565                     -1.608633    1.190025
                             /cut3 |   1.214853   .7141728                     -.1848996    2.614606
                             /cut4 |   3.379304    .714914                      1.978098     4.78051
----------------------------------------------------------------------------------------------------

. est sto boot_m4

. 
.   esttab boot_m1 boot_m2 boot_m3 boot_m4 using Table_B6.rtf,starlevels( * 0.05 ** 0.01) cells((b(star fmt(3
> )) ci_bc[ll] ci_bc[ul] )) ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Gov." "Gov. Staff" "Legis." "Legis. Staff" ) 
(output written to Table_B6.rtf)

. 
. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B7 ******
. 
.  ologit d_15a i.intersection i.reve_1a i.reve_1b i.civil_service weekly_hours age age_2 b3.edu years_employ
> _state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fu
> ncat13 i.state i.year, vce(boot, reps(1000) seed(55803)) 
(running ologit on estimation sample)

Bootstrap replications (1000)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400
..................................................   450
..................................................   500
..................................................   550
..................................................   600
..................................................   650
..................................................   700
..................................................   750
..................................................   800
..................................................   850
..................................................   900
..................................................   950
..................................................  1000

Ordered logistic regression                     Number of obs     =      6,224
                                                Replications      =      1,000
                                                Wald chi2(100)    =    1257.58
                                                Prob > chi2       =     0.0000
Log likelihood =  -5786.643                     Pseudo R2         =     0.0995

----------------------------------------------------------------------------------------------------
                                   |   Observed   Bootstrap                         Normal-based
                             d_15a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.1242675   .0817125    -1.52   0.128     -.284421     .035886
                     Man of Color  |   .3003436   .1191285     2.52   0.012     .0668561    .5338312
                   Woman of Color  |   .5525573   .2458796     2.25   0.025     .0706422    1.034472
                                   |
                           reve_1a |
                Less than Monthly  |    .242045    .085381     2.83   0.005     .0747013    .4093887
                          Monthly  |   .2699382   .1071801     2.52   0.012     .0598691    .4800073
                           Weekly  |   .5819831   .1355004     4.30   0.000     .3164072     .847559
                            Daily  |   1.462612   .3896162     3.75   0.000     .6989778    2.226245
                                   |
                           reve_1b |
                Less than Monthly  |   .3770689   .1971582     1.91   0.056    -.0093541     .763492
                          Monthly  |   .5959252   .1994429     2.99   0.003     .2050243    .9868261
                           Weekly  |   1.053024   .2054811     5.12   0.000     .6502883    1.455759
                            Daily  |   1.584073   .2256993     7.02   0.000      1.14171    2.026435
                                   |
                     civil_service |
                              Yes  |   .1646428   .0688101     2.39   0.017     .0297776    .2995081
                      weekly_hours |  -.0057133   .0036834    -1.55   0.121    -.0129326    .0015061
                               age |   .0131835    .025364     0.52   0.603    -.0365292    .0628961
                             age_2 |  -.0002081   .0002491    -0.84   0.404    -.0006964    .0002802
                                   |
                               edu |
              High school or less  |  -.0076404   .2695733    -0.03   0.977    -.5359944    .5207136
                     Some college  |   -.230757   .1383876    -1.67   0.095    -.5019918    .0404778
                   Graduate study  |   .1571962   .1002421     1.57   0.117    -.0392747    .3536672
                  Graduate degree  |   -.115084   .0777317    -1.48   0.139    -.2674353    .0372674
                                   |
                years_employ_state |  -.0007676   .0048148    -0.16   0.873    -.0102044    .0086692
               years_employ_agency |  -.0030764   .0052334    -0.59   0.557    -.0133337    .0071809
             years_employ_position |  -.0192047   .0064088    -3.00   0.003    -.0317656   -.0066437
                                   |
                              pid5 |
                       Republican  |  -.0104676   .0960937    -0.11   0.913    -.1988077    .1778725
                  Lean Republican  |  -.0427336   .1231891    -0.35   0.729    -.2841797    .1987126
                  Lean Democratic  |  -.0735414   .1162836    -0.63   0.527     -.301453    .1543701
                       Democratic  |  -.0795953   .0869265    -0.92   0.360    -.2499681    .0907775
                                   |
                       agency_size |
                           25-100  |   .0650051   .0900092     0.72   0.470    -.1114098    .2414199
                          101-500  |  -.0988579   .0999446    -0.99   0.323    -.2947458    .0970299
                        501-1,000  |  -.0928467   .1308372    -0.71   0.478    -.3492829    .1635896
                      1,001-5,000  |   -.202682   .1403129    -1.44   0.149    -.4776902    .0723263
                       Over 5,000  |  -.1535326   .1889959    -0.81   0.417    -.5239578    .2168927
                                   |
                 log_agency_budget |   .0477385   .0233126     2.05   0.041     .0020467    .0934304
                      inst6017_nom |  -.0016483    .003351    -0.49   0.623    -.0082162    .0049196
                                   |
                          funcat13 |
                    Staff: Fiscal  |   2.550807   .1889985    13.50   0.000     2.180376    2.921237
                Staff: Non-Fiscal  |   2.885916   .1910704    15.10   0.000     2.511425    3.260408
Income Security & Social Services  |   1.951379   .1559746    12.51   0.000     1.645674    2.257083
                        Education  |   1.757852   .1723454    10.20   0.000     1.420062    2.095643
                           Health  |   1.926734   .1628133    11.83   0.000     1.607626    2.245843
                Natural Resources  |    1.83691    .152919    12.01   0.000     1.537194    2.136625
             Environment & Energy  |   2.455734   .1569643    15.65   0.000     2.148089    2.763378
             Economic Development  |    2.17803   .1744973    12.48   0.000     1.836022    2.520038
                 Criminal Justice  |   2.211354   .1599216    13.83   0.000     1.897913    2.524794
                       Regulatory  |   1.790367    .148581    12.05   0.000     1.499153     2.08158
                   Transportation  |   2.335863   .1759159    13.28   0.000     1.991074    2.680652
                            Other  |   1.875953   .1600392    11.72   0.000     1.562282    2.189624
                                   |
                             state |
                               AK  |   1.118635   .2515065     4.45   0.000     .6256911    1.611578
                               AZ  |   .5056424   .2775498     1.82   0.068    -.0383451     1.04963
                               AR  |   .9488965   .2881033     3.29   0.001     .3842245    1.513569
                               CA  |   1.438984   .3107438     4.63   0.000     .8299374    2.048031
                               CO  |    .240694   .2594051     0.93   0.353    -.2677307    .7491187
                               CT  |   1.158903    .326298     3.55   0.000     .5193706    1.798435
                               DE  |   1.287364   .2547014     5.05   0.000     .7881589     1.78657
                               FL  |   .7672606   .2876844     2.67   0.008     .2034096    1.331112
                               GA  |   .9716983   .2772817     3.50   0.000     .4282362     1.51516
                               HI  |   1.161814   .2803649     4.14   0.000     .6123092    1.711319
                               ID  |   .5409002   .2549379     2.12   0.034      .041231    1.040569
                               IL  |   1.140007   .3198999     3.56   0.000     .5130148    1.766999
                               IN  |   1.034193   .2837305     3.64   0.000     .4780915    1.590295
                               IA  |   .7512684   .2561386     2.93   0.003     .2492461    1.253291
                               KS  |   1.132718   .2703291     4.19   0.000     .6028829    1.662554
                               KY  |   1.133183   .2821299     4.02   0.000     .5802184    1.686147
                               LA  |   .7583673   .3100796     2.45   0.014     .1506224    1.366112
                               ME  |   1.076142   .2966172     3.63   0.000     .4947831    1.657501
                               MD  |    1.28201    .264886     4.84   0.000     .7628435    1.801177
                               MA  |   .7257357   .2816851     2.58   0.010      .173643    1.277828
                               MI  |   1.238845    .262733     4.72   0.000     .7238981    1.753793
                               MN  |   .9016696   .2457891     3.67   0.000     .4199317    1.383407
                               MS  |  -.3741053   .2661459    -1.41   0.160    -.8957418    .1475312
                               MO  |   .8476494   .2643976     3.21   0.001     .3294396    1.365859
                               MT  |   .6210894   .2443921     2.54   0.011     .1420896    1.100089
                               NE  |   .8859937    .247843     3.57   0.000     .4002304    1.371757
                               NV  |   1.015144   .2683103     3.78   0.000     .4892651    1.541022
                               NH  |   .9847659   .2784712     3.54   0.000     .4389724    1.530559
                               NJ  |   1.618078   .3029215     5.34   0.000     1.024363    2.211793
                               NM  |   1.102043    .273552     4.03   0.000     .5658909    1.638195
                               NY  |   1.696496   .4330015     3.92   0.000      .847829    2.545164
                               NC  |   .7415078   .2436503     3.04   0.002      .263962    1.219054
                               ND  |   .5759193   .2515768     2.29   0.022     .0828379    1.069001
                               OH  |   .9131874    .281535     3.24   0.001      .361389    1.464986
                               OK  |   .2570393   .2500241     1.03   0.304    -.2329988    .7470775
                               OR  |   .6114015   .2510823     2.44   0.015     .1192892    1.103514
                               PA  |   1.204994   .2761669     4.36   0.000     .6637166    1.746271
                               RI  |   .9878919   .3027015     3.26   0.001     .3946079    1.581176
                               SC  |  -.0725063   .2652842    -0.27   0.785    -.5924537    .4474411
                               SD  |   1.077479   .2663199     4.05   0.000     .5555014    1.599456
                               TN  |   .9778272   .2694145     3.63   0.000     .4497845     1.50587
                               TX  |  -.3600298    .265889    -1.35   0.176    -.8811626     .161103
                               UT  |   .9676516   .2413759     4.01   0.000     .4945635     1.44074
                               VT  |   1.092281   .2815397     3.88   0.000     .5404732    1.644089
                               VA  |   1.171459   .2843155     4.12   0.000     .6142109    1.728707
                               WA  |   .8721144   .2702014     3.23   0.001     .3425294    1.401699
                               WV  |   .5587808   .2752804     2.03   0.042     .0192411    1.098321
                               WI  |   1.576222    .270843     5.82   0.000      1.04538    2.107065
                               WY  |   .5428254   .2582698     2.10   0.036     .0366258    1.049025
                                   |
                              year |
                             1984  |   .1462641   .1014982     1.44   0.150    -.0526687    .3451969
                             1988  |    .098596   .0995725     0.99   0.322    -.0965625    .2937546
                             1994  |    .450507   .1085202     4.15   0.000     .2378112    .6632028
                             1998  |   .6407183   .1181071     5.42   0.000     .4092326     .872204
                             2004  |   .2844813   .1150973     2.47   0.013     .0588948    .5100678
                             2008  |   .5527944   .1306706     4.23   0.000     .2966847     .808904
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -.0179737   .7267294                     -1.442337     1.40639
                             /cut2 |   1.955136    .729083                      .5261594    3.384112
                             /cut3 |   3.549956    .730516                      2.118171    4.981741
----------------------------------------------------------------------------------------------------

.  est sto boot_m5

. 
.  
.  ologit d_16a i.intersection i.reve_1c i.reve_1d  i.civil_service weekly_hours age age_2 b3.edu years_emplo
> y_state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.fu
> ncat13 i.state i.year, vce(boot, reps(1000) seed(55803)) 
(running ologit on estimation sample)

Bootstrap replications (1000)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400
..................................................   450
..................................................   500
..................................................   550
..................................................   600
..................................................   650
..................................................   700
..................................................   750
..................................................   800
..................................................   850
..................................................   900
..................................................   950
..................................................  1000

Ordered logistic regression                     Number of obs     =      6,200
                                                Replications      =      1,000
                                                Wald chi2(100)    =     428.43
                                                Prob > chi2       =     0.0000
Log likelihood =   -6424.02                     Pseudo R2         =     0.0331

----------------------------------------------------------------------------------------------------
                                   |   Observed   Bootstrap                         Normal-based
                             d_16a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |   .0369801   .0733897     0.50   0.614    -.1068611    .1808214
                     Man of Color  |   .2540965   .1157824     2.19   0.028     .0271673    .4810257
                   Woman of Color  |   .4311526   .2262809     1.91   0.057    -.0123498     .874655
                                   |
                           reve_1c |
                Less than Monthly  |  -.4533227    .278872    -1.63   0.104    -.9999018    .0932564
                          Monthly  |  -.3840042   .2797648    -1.37   0.170    -.9323332    .1643247
                           Weekly  |  -.2484308   .2841982    -0.87   0.382    -.8054491    .3085874
                            Daily  |  -.3010773   .3093541    -0.97   0.330    -.9074003    .3052456
                                   |
                           reve_1d |
                Less than Monthly  |   .5725446   .2182505     2.62   0.009     .1447816    1.000308
                          Monthly  |   .7406869   .2180318     3.40   0.001     .3133524    1.168021
                           Weekly  |   .9205621   .2220821     4.15   0.000     .4852892    1.355835
                            Daily  |   1.300182   .2456684     5.29   0.000     .8186813    1.781684
                                   |
                     civil_service |
                              Yes  |   .0752613   .0661132     1.14   0.255    -.0543181    .2048407
                      weekly_hours |  -.0017046    .003351    -0.51   0.611    -.0082724    .0048633
                               age |   .0471632   .0248478     1.90   0.058    -.0015376     .095864
                             age_2 |  -.0004258   .0002463    -1.73   0.084    -.0009086     .000057
                                   |
                               edu |
              High school or less  |    .037846   .2903256     0.13   0.896    -.5311818    .6068738
                     Some college  |  -.1283292   .1295777    -0.99   0.322    -.3822968    .1256385
                   Graduate study  |   .0548737   .0876526     0.63   0.531    -.1169223    .2266697
                  Graduate degree  |   -.072935   .0732209    -1.00   0.319    -.2164454    .0705754
                                   |
                years_employ_state |   .0083404   .0045021     1.85   0.064    -.0004835    .0171644
               years_employ_agency |  -.0100326   .0047999    -2.09   0.037    -.0194401    -.000625
             years_employ_position |  -.0089602   .0062241    -1.44   0.150    -.0211592    .0032388
                                   |
                              pid5 |
                       Republican  |   -.153614    .089881    -1.71   0.087    -.3297775    .0225495
                  Lean Republican  |   .0157165   .1175781     0.13   0.894    -.2147324    .2461653
                  Lean Democratic  |   .0319403   .1111936     0.29   0.774    -.1859952    .2498759
                       Democratic  |  -.0824199   .0876579    -0.94   0.347    -.2542262    .0893865
                                   |
                       agency_size |
                           25-100  |   .1047572   .0812309     1.29   0.197    -.0544523    .2639668
                          101-500  |    .105171   .0962066     1.09   0.274    -.0833905    .2937324
                        501-1,000  |  -.0853345   .1274014    -0.67   0.503    -.3350367    .1643676
                      1,001-5,000  |   -.170412   .1317881    -1.29   0.196    -.4287121     .087888
                       Over 5,000  |  -.1603723   .1804758    -0.89   0.374    -.5140983    .1933537
                                   |
                 log_agency_budget |   .0351698   .0220228     1.60   0.110     -.007994    .0783337
                      inst6017_nom |   .0080557   .0033571     2.40   0.016     .0014758    .0146356
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.0780437   .1721201    -0.45   0.650    -.4153929    .2593056
                Staff: Non-Fiscal  |   .0178142   .1799708     0.10   0.921    -.3349221    .3705506
Income Security & Social Services  |  -.1699223   .1694545    -1.00   0.316    -.5020469    .1622024
                        Education  |   .0927977    .190242     0.49   0.626    -.2800698    .4656651
                           Health  |   .0115461    .182772     0.06   0.950    -.3466805    .3697727
                Natural Resources  |  -.2611242   .1521143    -1.72   0.086    -.5592627    .0370144
             Environment & Energy  |   .1012103   .1667121     0.61   0.544    -.2255395    .4279601
             Economic Development  |  -.3359153    .171824    -1.95   0.051    -.6726841    .0008536
                 Criminal Justice  |   .2113475   .1698157     1.24   0.213    -.1214852    .5441802
                       Regulatory  |     .02643    .160348     0.16   0.869    -.2878463    .3407063
                   Transportation  |   .0761095    .176294     0.43   0.666    -.2694203    .4216393
                            Other  |  -.4628175   .1654385    -2.80   0.005    -.7870709   -.1385641
                                   |
                             state |
                               AK  |     .76302   .2390822     3.19   0.001     .2944276    1.231612
                               AZ  |   .8282129   .2654699     3.12   0.002     .3079015    1.348524
                               AR  |   .6244279   .2522488     2.48   0.013     .1300294    1.118826
                               CA  |   .8294245   .2795748     2.97   0.003     .2814679    1.377381
                               CO  |    1.01677   .2570606     3.96   0.000     .5129409      1.5206
                               CT  |   .8345932   .2994559     2.79   0.005     .2476703    1.421516
                               DE  |   .9237991    .247438     3.73   0.000     .4388296    1.408769
                               FL  |   1.171684   .2608629     4.49   0.000     .6604026    1.682966
                               GA  |   .5026266     .26675     1.88   0.060    -.0201938    1.025447
                               HI  |   .5385426   .2656212     2.03   0.043     .0179346    1.059151
                               ID  |   .7519688   .2505917     3.00   0.003      .260818     1.24312
                               IL  |   .4156331   .2782735     1.49   0.135    -.1297731    .9610392
                               IN  |   .5850284   .2488739     2.35   0.019     .0972445    1.072812
                               IA  |   .9377369   .2444621     3.84   0.000        .4586    1.416874
                               KS  |   1.237952   .2553529     4.85   0.000     .7374694    1.738434
                               KY  |   .5273884   .2416687     2.18   0.029     .0537264     1.00105
                               LA  |   .1453688   .2652932     0.55   0.584    -.3745963    .6653339
                               ME  |   1.153925    .279266     4.13   0.000     .6065733    1.701276
                               MD  |   .4841354   .2640139     1.83   0.067    -.0333223    1.001593
                               MA  |  -.0304925   .2574479    -0.12   0.906    -.5350812    .4740962
                               MI  |   .1584447   .2470289     0.64   0.521     -.325723    .6426124
                               MN  |   1.195355   .2379983     5.02   0.000     .7288872    1.661823
                               MS  |   .9439424   .2619399     3.60   0.000     .4305497    1.457335
                               MO  |   .4462451   .2493735     1.79   0.074    -.0425181    .9350083
                               MT  |   .7373892   .2297646     3.21   0.001     .2870589    1.187719
                               NE  |   1.028459   .2612708     3.94   0.000     .5163774     1.54054
                               NV  |   .9976947   .2431671     4.10   0.000     .5210959    1.474293
                               NH  |   1.320917   .2673925     4.94   0.000     .7968374    1.844997
                               NJ  |   .7615457   .2641118     2.88   0.004     .2438961    1.279195
                               NM  |   .7259687   .2643923     2.75   0.006     .2077694    1.244168
                               NY  |   .5955434   .2820744     2.11   0.035     .0426876    1.148399
                               NC  |   .8279354   .2270469     3.65   0.000     .3829317    1.272939
                               ND  |   .8598149   .2406397     3.57   0.000     .3881698     1.33146
                               OH  |   .4276222   .2526452     1.69   0.091    -.0675532    .9227977
                               OK  |    1.25129   .2591572     4.83   0.000     .7433512    1.759229
                               OR  |   1.353209   .2553906     5.30   0.000     .8526528    1.853766
                               PA  |   .0842203   .2381046     0.35   0.724    -.3824562    .5508968
                               RI  |   .4250767   .2717847     1.56   0.118    -.1076116     .957765
                               SC  |   .7896953   .2705886     2.92   0.004     .2593514    1.320039
                               SD  |   .4696611   .2351524     2.00   0.046     .0087708    .9305514
                               TN  |   .2094934   .2490786     0.84   0.400    -.2786917    .6976784
                               TX  |   1.281149   .2661523     4.81   0.000     .7594999    1.802798
                               UT  |   1.152184   .2389413     4.82   0.000      .683868    1.620501
                               VT  |   .7151062   .2431426     2.94   0.003     .2385553    1.191657
                               VA  |   .9988064   .2600274     3.84   0.000     .4891621    1.508451
                               WA  |   .8397862    .264822     3.17   0.002     .3207447    1.358828
                               WV  |   .6028848   .2497372     2.41   0.016     .1134089    1.092361
                               WI  |   .7353899   .2430652     3.03   0.002     .2589908    1.211789
                               WY  |    .773118   .2502082     3.09   0.002     .2827189    1.263517
                                   |
                              year |
                             1984  |   .0414154   .0967887     0.43   0.669     -.148287    .2311178
                             1988  |   .0053983   .0895991     0.06   0.952    -.1702128    .1810094
                             1994  |   .1720171   .0969679     1.77   0.076    -.0180365    .3620707
                             1998  |   .3386069   .1016087     3.33   0.001     .1394574    .5377563
                             2004  |    .074874   .1094709     0.68   0.494     -.139685     .289433
                             2008  |   .2286511   .1191248     1.92   0.055    -.0048291    .4621314
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.179245   .7609537                     -2.670687    .3121969
                             /cut2 |   1.088142   .7585738                     -.3986354    2.574919
                             /cut3 |    2.95614   .7590411                      1.468447    4.443834
----------------------------------------------------------------------------------------------------

.  est sto boot_m6

. 
.  
.  ologit d_20a i.intersection i.reve_1a i.reve_1b i.civil_service weekly_hours age age_2 b3.edu years_employ
> _state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fu
> ncat13 i.state i.year, vce(boot, reps(1000) seed(55803)) 
(running ologit on estimation sample)

Bootstrap replications (1000)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400
..................................................   450
..................................................   500
..................................................   550
..................................................   600
..................................................   650
..................................................   700
..................................................   750
..................................................   800
..................................................   850
..................................................   900
..................................................   950
..................................................  1000

Ordered logistic regression                     Number of obs     =      6,175
                                                Replications      =      1,000
                                                Wald chi2(100)    =    1005.39
                                                Prob > chi2       =     0.0000
Log likelihood = -7501.4509                     Pseudo R2         =     0.0619

----------------------------------------------------------------------------------------------------
                                   |   Observed   Bootstrap                         Normal-based
                             d_20a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |   -.223584   .0719515    -3.11   0.002    -.3646063   -.0825616
                     Man of Color  |   .2070339   .1055844     1.96   0.050     .0000923    .4139754
                   Woman of Color  |    .498217   .1991229     2.50   0.012     .1079432    .8884908
                                   |
                           reve_1a |
                Less than Monthly  |   .2163756   .0764503     2.83   0.005     .0665356    .3662155
                          Monthly  |   .2735757   .0994257     2.75   0.006     .0787048    .4684465
                           Weekly  |   .4128912   .1241238     3.33   0.001     .1696129    .6561694
                            Daily  |    .620476   .2195763     2.83   0.005     .1901143    1.050838
                                   |
                           reve_1b |
                Less than Monthly  |    .237213   .1966633     1.21   0.228      -.14824    .6226659
                          Monthly  |   .4180031   .2014374     2.08   0.038     .0231929    .8128132
                           Weekly  |   .6419187   .2031568     3.16   0.002     .2437387    1.040099
                            Daily  |   .8702175    .219787     3.96   0.000      .439443    1.300992
                                   |
                     civil_service |
                              Yes  |   .2147597   .0653097     3.29   0.001     .0867551    .3427644
                      weekly_hours |  -.0013704   .0032136    -0.43   0.670    -.0076689    .0049281
                               age |  -.0225404    .024258    -0.93   0.353    -.0700852    .0250045
                             age_2 |   .0001661   .0002402     0.69   0.489    -.0003047     .000637
                                   |
                               edu |
              High school or less  |   .3539448   .2747584     1.29   0.198    -.1845718    .8924615
                     Some college  |   -.054266     .13255    -0.41   0.682    -.3140593    .2055272
                   Graduate study  |   -.018186   .0838438    -0.22   0.828     -.182517    .1461449
                  Graduate degree  |  -.2479807   .0718426    -3.45   0.001    -.3887897   -.1071718
                                   |
                years_employ_state |   .0010563   .0043858     0.24   0.810    -.0075398    .0096523
               years_employ_agency |  -.0007916   .0046762    -0.17   0.866    -.0099567    .0083736
             years_employ_position |  -.0247561   .0060823    -4.07   0.000    -.0366773   -.0128349
                                   |
                              pid5 |
                       Republican  |   .1278304   .0861836     1.48   0.138    -.0410864    .2967471
                  Lean Republican  |   .0687908   .1109326     0.62   0.535    -.1486331    .2862147
                  Lean Democratic  |   .0815911    .099835     0.82   0.414    -.1140818    .2772641
                       Democratic  |    .065322   .0824332     0.79   0.428    -.0962442    .2268881
                                   |
                       agency_size |
                           25-100  |  -.1020634    .081657    -1.25   0.211    -.2621081    .0579814
                          101-500  |  -.2622672   .0874102    -3.00   0.003     -.433588   -.0909465
                        501-1,000  |  -.3807955   .1111655    -3.43   0.001     -.598676   -.1629151
                      1,001-5,000  |  -.4358469   .1212398    -3.59   0.000    -.6734726   -.1982212
                       Over 5,000  |   -.466413   .1638925    -2.85   0.004    -.7876365   -.1451896
                                   |
                 log_agency_budget |   .0012167   .0194229     0.06   0.950    -.0368515    .0392849
                      inst6017_nom |  -.0038087   .0029807    -1.28   0.201    -.0096507    .0020334
                                   |
                          funcat13 |
                    Staff: Fiscal  |   2.124618   .1819978    11.67   0.000     1.767908    2.481327
                Staff: Non-Fiscal  |   2.493533   .1817738    13.72   0.000     2.137263    2.849804
Income Security & Social Services  |      1.855   .1711947    10.84   0.000     1.519465    2.190536
                        Education  |   1.484903   .1743102     8.52   0.000     1.143262    1.826545
                           Health  |   1.868607   .1757162    10.63   0.000      1.52421    2.213005
                Natural Resources  |   1.646815   .1635362    10.07   0.000      1.32629     1.96734
             Environment & Energy  |   1.743706   .1671772    10.43   0.000     1.416045    2.071367
             Economic Development  |   1.721396   .1749404     9.84   0.000     1.378519    2.064273
                 Criminal Justice  |    1.75042    .169136    10.35   0.000      1.41892    2.081921
                       Regulatory  |   1.200937     .16037     7.49   0.000     .8866172    1.515256
                   Transportation  |   1.826961   .1723862    10.60   0.000      1.48909    2.164831
                            Other  |   1.797854   .1806985     9.95   0.000     1.443691    2.152016
                                   |
                             state |
                               AK  |   1.082661    .250005     4.33   0.000       .59266    1.572661
                               AZ  |   .5358674   .2719102     1.97   0.049     .0029331    1.068802
                               AR  |   .7669651   .2620502     2.93   0.003     .2533561    1.280574
                               CA  |   1.183997   .3079806     3.84   0.000     .5803665    1.787628
                               CO  |  -.4967529   .2533757    -1.96   0.050    -.9933602   -.0001457
                               CT  |   .3940912   .3109934     1.27   0.205    -.2154447    1.003627
                               DE  |    .476991   .2462159     1.94   0.053    -.0055834    .9595654
                               FL  |   .6012339   .2539848     2.37   0.018     .1034329    1.099035
                               GA  |   .5573796    .251215     2.22   0.027     .0650073    1.049752
                               HI  |   1.198756   .2690394     4.46   0.000     .6714481    1.726063
                               ID  |   .2417442    .249382     0.97   0.332    -.2470355    .7305239
                               IL  |   .7088106   .2921243     2.43   0.015     .1362574    1.281364
                               IN  |   1.336694   .2590501     5.16   0.000     .8289656    1.844423
                               IA  |   .5559855   .2321239     2.40   0.017     .1010311     1.01094
                               KS  |   .4877769   .2663293     1.83   0.067    -.0342189    1.009773
                               KY  |   1.255336   .2711764     4.63   0.000     .7238401    1.786832
                               LA  |   .6105656   .2666919     2.29   0.022     .0878592    1.133272
                               ME  |   .0463092   .2671246     0.17   0.862    -.4772453    .5698637
                               MD  |   .6060077   .2714133     2.23   0.026     .0740473    1.137968
                               MA  |    .893062   .2899268     3.08   0.002     .3248159    1.461308
                               MI  |   .9795158   .2512419     3.90   0.000     .4870908    1.471941
                               MN  |  -.0030547   .2363223    -0.01   0.990    -.4662379    .4601285
                               MS  |  -.3379897   .2737694    -1.23   0.217    -.8745678    .1985885
                               MO  |   .3819967   .2482639     1.54   0.124    -.1045915     .868585
                               MT  |   .1827803   .2433408     0.75   0.453    -.2941588    .6597195
                               NE  |   .8011606   .2514846     3.19   0.001     .3082598    1.294061
                               NV  |   .5596408   .2506907     2.23   0.026     .0682962    1.050986
                               NH  |   .0642769   .2489994     0.26   0.796     -.423753    .5523067
                               NJ  |   1.255438   .2756697     4.55   0.000     .7151358    1.795741
                               NM  |   .4022057   .2692906     1.49   0.135    -.1255942    .9300057
                               NY  |   1.215348    .308414     3.94   0.000     .6108682    1.819829
                               NC  |   .5109553   .2311857     2.21   0.027     .0578396     .964071
                               ND  |   .2090441   .2536815     0.82   0.410    -.2881626    .7062508
                               OH  |   .6331062   .2427981     2.61   0.009     .1572308    1.108982
                               OK  |   .7097933   .2730255     2.60   0.009     .1746732    1.244913
                               OR  |   .2320357   .2363503     0.98   0.326    -.2312024    .6952737
                               PA  |   1.323251   .2593626     5.10   0.000     .8149099    1.831593
                               RI  |   .5613417   .2710779     2.07   0.038     .0300388    1.092645
                               SC  |   .0470551   .2458595     0.19   0.848    -.4348207    .5289309
                               SD  |   .5831734   .2539123     2.30   0.022     .0855145    1.080832
                               TN  |   .9640615   .2762287     3.49   0.000     .4226632     1.50546
                               TX  |  -.1015078   .2574057    -0.39   0.693    -.6060136     .402998
                               UT  |   .6428746    .231459     2.78   0.005     .1892233    1.096526
                               VT  |   .6846565   .2553941     2.68   0.007     .1840933     1.18522
                               VA  |   1.276843   .2791174     4.57   0.000     .7297831    1.823903
                               WA  |   .3305411   .2560707     1.29   0.197    -.1713483    .8324306
                               WV  |   .4697377   .2609807     1.80   0.072     -.041775    .9812504
                               WI  |   .7184615   .2309027     3.11   0.002     .2659006    1.171022
                               WY  |   .8312287   .2554637     3.25   0.001     .3305291    1.331928
                                   |
                              year |
                             1984  |  -.0498976   .0993924    -0.50   0.616    -.2447031    .1449079
                             1988  |  -.1935672   .0921665    -2.10   0.036    -.3742101   -.0129242
                             1994  |   .2769455   .0993839     2.79   0.005     .0821566    .4717343
                             1998  |   .4274018   .1022179     4.18   0.000     .2270584    .6277453
                             2004  |  -.0701028   .1054103    -0.67   0.506    -.2767032    .1364976
                             2008  |   .2888849   .1135462     2.54   0.011     .0663384    .5114315
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -.8877279   .6543223                     -2.170176    .3947203
                             /cut2 |   1.281446   .6540824                     -.0005318    2.563424
                             /cut3 |   2.772505   .6537755                      1.491128    4.053881
----------------------------------------------------------------------------------------------------

.  est sto boot_m7

. 
.  ologit d_21a i.intersection i.reve_1c i.reve_1d  i.civil_service weekly_hours age age_2 b3.edu years_emplo
> y_state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.f
> uncat13 i.state i.year, vce(boot, reps(1000) seed(55803)) 
(running ologit on estimation sample)

Bootstrap replications (1000)
----+--- 1 ---+--- 2 ---+--- 3 ---+--- 4 ---+--- 5 
..................................................    50
..................................................   100
..................................................   150
..................................................   200
..................................................   250
..................................................   300
..................................................   350
..................................................   400
..................................................   450
..................................................   500
..................................................   550
..................................................   600
..................................................   650
..................................................   700
..................................................   750
..................................................   800
..................................................   850
..................................................   900
..................................................   950
..................................................  1000

Ordered logistic regression                     Number of obs     =      6,158
                                                Replications      =      1,000
                                                Wald chi2(100)    =     472.41
                                                Prob > chi2       =     0.0000
Log likelihood = -7466.6454                     Pseudo R2         =     0.0291

----------------------------------------------------------------------------------------------------
                                   |   Observed   Bootstrap                         Normal-based
                             d_21a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
                      intersection |
                      White Woman  |  -.0786444   .0673688    -1.17   0.243    -.2106848     .053396
                     Man of Color  |   .3410724   .1009671     3.38   0.001     .1431806    .5389642
                   Woman of Color  |   .5717724    .206737     2.77   0.006     .1665753    .9769696
                                   |
                           reve_1c |
                Less than Monthly  |     .10925   .2866678     0.38   0.703    -.4526086    .6711085
                          Monthly  |   .0470158   .2862476     0.16   0.870    -.5140191    .6080508
                           Weekly  |   .1109519   .2881336     0.39   0.700    -.4537796    .6756834
                            Daily  |   .0685312   .3004205     0.23   0.820    -.5202822    .6573446
                                   |
                           reve_1d |
                Less than Monthly  |    .718949   .2234245     3.22   0.001     .2810451    1.156853
                          Monthly  |   .8841762   .2226606     3.97   0.000     .4477696    1.320583
                           Weekly  |   .9600296   .2269724     4.23   0.000     .5151718    1.404887
                            Daily  |   1.183061   .2464053     4.80   0.000     .7001157    1.666007
                                   |
                     civil_service |
                              Yes  |   .0913557   .0629329     1.45   0.147    -.0319905    .2147019
                      weekly_hours |   .0013429   .0031557     0.43   0.670    -.0048421    .0075279
                               age |  -.0234925   .0247887    -0.95   0.343    -.0720773    .0250924
                             age_2 |   .0002765   .0002471     1.12   0.263    -.0002078    .0007608
                                   |
                               edu |
              High school or less  |   .3188953   .2875804     1.11   0.267    -.2447519    .8825425
                     Some college  |  -.2334719   .1290695    -1.81   0.070    -.4864435    .0194997
                   Graduate study  |  -.0872736   .0847221    -1.03   0.303    -.2533258    .0787786
                  Graduate degree  |  -.2556885    .066349    -3.85   0.000    -.3857301   -.1256469
                                   |
                years_employ_state |  -.0051609   .0040218    -1.28   0.199    -.0130435    .0027217
               years_employ_agency |   .0058361      .0043     1.36   0.175    -.0025917    .0142639
             years_employ_position |  -.0139081   .0064707    -2.15   0.032    -.0265905   -.0012257
                                   |
                              pid5 |
                       Republican  |  -.0199526    .088854    -0.22   0.822    -.1941033    .1541982
                  Lean Republican  |   .0955725   .1196256     0.80   0.424    -.1388893    .3300343
                  Lean Democratic  |   .1091993   .1035311     1.05   0.292    -.0937178    .3121165
                       Democratic  |   .0064929   .0812556     0.08   0.936    -.1527651     .165751
                                   |
                       agency_size |
                           25-100  |   .1225227   .0821257     1.49   0.136    -.0384407    .2834861
                          101-500  |   .1092047   .0900141     1.21   0.225    -.0672198    .2856291
                        501-1,000  |  -.0804772   .1134259    -0.71   0.478    -.3027879    .1418335
                      1,001-5,000  |  -.0954097   .1189412    -0.80   0.422    -.3285302    .1377108
                       Over 5,000  |  -.1316604   .1644345    -0.80   0.423     -.453946    .1906252
                                   |
                 log_agency_budget |   .0190175   .0215145     0.88   0.377    -.0231502    .0611852
                      inst6017_nom |   .0036674   .0030672     1.20   0.232    -.0023441    .0096789
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .2065958   .1742231     1.19   0.236    -.1348752    .5480669
                Staff: Non-Fiscal  |    .324499   .1798902     1.80   0.071    -.0280793    .6770772
Income Security & Social Services  |   .1536282   .1612351     0.95   0.341    -.1623868    .4696432
                        Education  |   .1997398   .1794275     1.11   0.266    -.1519317    .5514113
                           Health  |   .2854157   .1770473     1.61   0.107    -.0615906    .6324219
                Natural Resources  |   .3496089   .1543187     2.27   0.023     .0471498     .652068
             Environment & Energy  |   .4458211   .1611248     2.77   0.006     .1300223    .7616199
             Economic Development  |   .1203173   .1675122     0.72   0.473    -.2080006    .4486352
                 Criminal Justice  |  -.0118803   .1729401    -0.07   0.945    -.3508368    .3270761
                       Regulatory  |   .0430467   .1603309     0.27   0.788    -.2711961    .3572894
                   Transportation  |   .4118565   .1746324     2.36   0.018     .0695833    .7541297
                            Other  |   .2781264   .1685869     1.65   0.099    -.0522979    .6085507
                                   |
                             state |
                               AK  |    .151369   .2292231     0.66   0.509       -.2979    .6006381
                               AZ  |   .1664503   .2642036     0.63   0.529    -.3513793    .6842798
                               AR  |   .7847349   .2608384     3.01   0.003      .273501    1.295969
                               CA  |   .1623595   .2603825     0.62   0.533    -.3479809    .6726999
                               CO  |   .0201354    .240389     0.08   0.933    -.4510184    .4912891
                               CT  |   .9054051   .2994672     3.02   0.002     .3184602     1.49235
                               DE  |   .2269869   .2411441     0.94   0.347    -.2456469    .6996207
                               FL  |   .5703886   .2626362     2.17   0.030      .055631    1.085146
                               GA  |   .2438811   .2448719     1.00   0.319     -.236059    .7238212
                               HI  |  -.2847697   .2500808    -1.14   0.255     -.774919    .2053796
                               ID  |   .8395376   .2467975     3.40   0.001     .3558233    1.323252
                               IL  |   .3553761   .2599101     1.37   0.172    -.1540384    .8647906
                               IN  |   .2373381   .2492667     0.95   0.341    -.2512156    .7258919
                               IA  |   .8997025   .2170691     4.14   0.000     .4742549     1.32515
                               KS  |   1.002167   .2399754     4.18   0.000     .5318234     1.47251
                               KY  |   1.031324   .2420193     4.26   0.000     .5569745    1.505673
                               LA  |   .4511873    .257344     1.75   0.080    -.0531976    .9555723
                               ME  |   .2937345   .2610608     1.13   0.261    -.2179352    .8054042
                               MD  |   .6435443   .2478505     2.60   0.009     .1577662    1.129322
                               MA  |  -.1271917   .2483801    -0.51   0.609    -.6140078    .3596244
                               MI  |   .9426299   .2468892     3.82   0.000      .458736    1.426524
                               MN  |   .0907566   .2272748     0.40   0.690    -.3546938    .5362071
                               MS  |   .4752427    .260093     1.83   0.068    -.0345301    .9850156
                               MO  |   .2561405   .2331477     1.10   0.272    -.2008207    .7131017
                               MT  |    .050391   .2296521     0.22   0.826    -.3997189    .5005008
                               NE  |   .2033564   .2488758     0.82   0.414    -.2844311     .691144
                               NV  |   .3883154    .245065     1.58   0.113    -.0920032    .8686339
                               NH  |   1.111596   .2621796     4.24   0.000     .5977333    1.625458
                               NJ  |   .4530862   .2600702     1.74   0.081     -.056642    .9628144
                               NM  |  -.3530254   .2609337    -1.35   0.176     -.864446    .1583953
                               NY  |   .2095196   .2819727     0.74   0.457    -.3431367    .7621759
                               NC  |   .4407452   .2225151     1.98   0.048     .0046235    .8768668
                               ND  |   .2852265   .2266191     1.26   0.208    -.1589388    .7293918
                               OH  |   .6693656   .2408277     2.78   0.005     .1973519    1.141379
                               OK  |   .8321741    .240827     3.46   0.001     .3601619    1.304186
                               OR  |    .096219   .2305198     0.42   0.676    -.3555916    .5480295
                               PA  |   .2486274   .2569276     0.97   0.333    -.2549414    .7521961
                               RI  |   .0582583   .2529005     0.23   0.818    -.4374175    .5539342
                               SC  |   1.110323   .2813237     3.95   0.000     .5589384    1.661707
                               SD  |   .2217329   .2572889     0.86   0.389    -.2825442    .7260099
                               TN  |   .8347342   .2553866     3.27   0.001     .3341857    1.335283
                               TX  |   .6655271   .2675501     2.49   0.013     .1411384    1.189916
                               UT  |   .4863982   .2320195     2.10   0.036     .0316484    .9411481
                               VT  |   .7888288    .242822     3.25   0.001     .3129064    1.264751
                               VA  |    .410458   .2844549     1.44   0.149    -.1470634    .9679794
                               WA  |  -.1194843   .2397013    -0.50   0.618    -.5892903    .3503216
                               WV  |   1.082288   .2467119     4.39   0.000      .598742    1.565835
                               WI  |   .8547203   .2220834     3.85   0.000     .4194448    1.289996
                               WY  |   .4220065   .2343149     1.80   0.072    -.0372422    .8812552
                                   |
                              year |
                             1984  |  -.2033245    .092704    -2.19   0.028     -.385021   -.0216279
                             1988  |  -.1906196    .090997    -2.09   0.036    -.3689704   -.0122688
                             1994  |   .0739387    .096005     0.77   0.441    -.1142277    .2621052
                             1998  |   .2198158   .1003076     2.19   0.028     .0232166    .4164151
                             2004  |  -.1682372   .1094519    -1.54   0.124    -.3827591    .0462846
                             2008  |   .2292203   .1168266     1.96   0.050     .0002443    .4581963
-----------------------------------+----------------------------------------------------------------
                             /cut1 |  -1.591533   .7533908                     -3.068152    -.114914
                             /cut2 |   .7532006   .7474154                     -.7117067    2.218108
                             /cut3 |   2.402633   .7474453                      .9376673    3.867599
----------------------------------------------------------------------------------------------------

.  est sto boot_m8

.  
.  esttab boot_m5 boot_m6 boot_m7 boot_m8 using Table_B7.rtf,starlevels( * 0.05 ** 0.01) cells((b(star fmt(3)
> ) ci_bc[ll] ci_bc[ul] )) ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Gov. Policy" "Legis. Policy" "Gov. Regs" "Legis. Regs" ) 
(output written to Table_B7.rtf)

. 
. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B8 ******
. mlogit reve_1a i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r, base(3)  r 

Iteration 0:   log pseudolikelihood = -10356.699  
Iteration 1:   log pseudolikelihood = -9055.8092  
Iteration 2:   log pseudolikelihood = -8487.4129  
Iteration 3:   log pseudolikelihood = -8402.5552  
Iteration 4:   log pseudolikelihood = -8385.8076  
Iteration 5:   log pseudolikelihood = -8385.3719  
Iteration 6:   log pseudolikelihood = -8385.2758  
Iteration 7:   log pseudolikelihood = -8385.2532  
Iteration 8:   log pseudolikelihood = -8385.2485  
Iteration 9:   log pseudolikelihood = -8385.2477  
Iteration 10:  log pseudolikelihood = -8385.2476  
Iteration 11:  log pseudolikelihood = -8385.2476  

Multinomial logistic regression                 Number of obs     =      7,515
                                                Wald chi2(372)    =    7059.29
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -8385.2476               Pseudo R2         =     0.1904

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
Never                              |
                      intersection |
                      White Woman  |   .1559192   .1281584     1.22   0.224    -.0952666     .407105
                     Man of Color  |   .0107544   .1929547     0.06   0.956    -.3674299    .3889387
                   Woman of Color  |   .4347069   .3535645     1.23   0.219    -.2582668    1.127681
                                   |
                     civil_service |
                              Yes  |   1.465533    .107854    13.59   0.000     1.254143    1.676923
                      weekly_hours |  -.0619051   .0059934   -10.33   0.000     -.073652   -.0501582
                               age |  -.0271117   .0409517    -0.66   0.508    -.1073756    .0531522
                             age_2 |   -.000018    .000406    -0.04   0.965    -.0008138    .0007778
                                   |
                               edu |
              High school or less  |   .1766614   .3790745     0.47   0.641     -.566311    .9196337
                     Some college  |  -.4540823   .2041624    -2.22   0.026    -.8542333   -.0539313
                   Graduate study  |  -.1575781   .1501251    -1.05   0.294    -.4518178    .1366616
                  Graduate degree  |   .0907462   .1208227     0.75   0.453    -.1460619    .3275544
                                   |
                years_employ_state |   .0070963   .0077995     0.91   0.363    -.0081904     .022383
               years_employ_agency |    .045957   .0082363     5.58   0.000     .0298142    .0620998
             years_employ_position |  -.0273448   .0107967    -2.53   0.011    -.0485059   -.0061838
                                   |
                              pid5 |
                       Republican  |   -.747178   .1534292    -4.87   0.000    -1.047894   -.4464622
                  Lean Republican  |  -.3321804   .1917949    -1.73   0.083    -.7080914    .0437306
                  Lean Democratic  |    -.07189   .1837992    -0.39   0.696    -.4321298    .2883498
                       Democratic  |   -.710198   .1419244    -5.00   0.000    -.9883647   -.4320312
                                   |
                       agency_size |
                           25-100  |   -.337668   .1319939    -2.56   0.011    -.5963712   -.0789648
                          101-500  |  -.9023053   .1560684    -5.78   0.000    -1.208194   -.5964168
                        501-1,000  |  -1.391888   .2135702    -6.52   0.000    -1.810478   -.9732984
                      1,001-5,000  |  -1.970481   .2293207    -8.59   0.000    -2.419942   -1.521021
                       Over 5,000  |  -2.400865   .3646403    -6.58   0.000    -3.115547   -1.686183
                                   |
                 log_agency_budget |  -.2479327   .0385568    -6.43   0.000    -.3235026   -.1723628
                      inst6017_nom |  -.0030661   .0052728    -0.58   0.561    -.0134006    .0072684
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.0216446   .3209461    -0.07   0.946    -.6506874    .6073983
                Staff: Non-Fiscal  |    .712601   .3005193     2.37   0.018     .1235941    1.301608
Income Security & Social Services  |   1.925629   .2780538     6.93   0.000     1.380653    2.470604
                        Education  |   .7806727   .3128408     2.50   0.013      .167516    1.393829
                           Health  |   2.089895   .2935988     7.12   0.000     1.514452    2.665338
                Natural Resources  |    .839397   .2575332     3.26   0.001     .3346412    1.344153
             Environment & Energy  |   .8511041   .2627149     3.24   0.001     .3361924    1.366016
             Economic Development  |  -.3386132    .303218    -1.12   0.264    -.9329096    .2556831
                 Criminal Justice  |   .8851837   .2734178     3.24   0.001     .3492946    1.421073
                       Regulatory  |   1.505471   .2510021     6.00   0.000     1.013516    1.997426
                   Transportation  |   1.055541   .2945551     3.58   0.000     .4782232    1.632858
                            Other  |    .705116   .2734629     2.58   0.010     .1691386    1.241093
                                   |
                             state |
                               AK  |   .7641428   .4653343     1.64   0.101    -.1478957    1.676181
                               AZ  |   1.315555   .4328333     3.04   0.002     .4672176    2.163893
                               AR  |  -.2470682   .4510309    -0.55   0.584    -1.131073    .6369361
                               CA  |   3.422259   .4550537     7.52   0.000      2.53037    4.314148
                               CO  |  -.0268363   .4337649    -0.06   0.951    -.8769998    .8233273
                               CT  |   1.329136   .4674475     2.84   0.004     .4129558    2.245316
                               DE  |   .2058872   .4758581     0.43   0.665    -.7267775    1.138552
                               FL  |   2.307773   .4460305     5.17   0.000     1.433569    3.181976
                               GA  |   .8781131   .4561058     1.93   0.054    -.0158379    1.772064
                               HI  |   1.362221   .4768352     2.86   0.004     .4276408    2.296801
                               ID  |  -.9391349   .4696715    -2.00   0.046    -1.859674   -.0185956
                               IL  |   1.675657   .4515314     3.71   0.000     .7906718    2.560643
                               IN  |   .9453616   .4476328     2.11   0.035     .0680174    1.822706
                               IA  |  -.3187712    .442021    -0.72   0.471    -1.185116     .547574
                               KS  |   .1984013   .4243218     0.47   0.640    -.6332543    1.030057
                               KY  |   1.423788   .4413232     3.23   0.001     .5588103    2.288765
                               LA  |   1.370385   .4785342     2.86   0.004      .432475    2.308294
                               ME  |  -.0376247    .483149    -0.08   0.938    -.9845793    .9093299
                               MD  |   2.017773   .4662149     4.33   0.000     1.104008    2.931537
                               MA  |   2.165891   .4503565     4.81   0.000     1.283209    3.048574
                               MI  |   .8248811   .4155904     1.98   0.047     .0103388    1.639423
                               MN  |   1.112648   .4431321     2.51   0.012     .2441246     1.98117
                               MS  |   .1676834   .4353257     0.39   0.700    -.6855392    1.020906
                               MO  |   1.420921   .4267982     3.33   0.001     .5844123    2.257431
                               MT  |   -.585241   .4229423    -1.38   0.166    -1.414193    .2437106
                               NE  |   .2274661   .4351398     0.52   0.601    -.6253922    1.080324
                               NV  |  -.1460964   .4563214    -0.32   0.749     -1.04047    .7482772
                               NH  |  -.1410191    .459074    -0.31   0.759    -1.040788    .7587494
                               NJ  |   2.310289   .4614615     5.01   0.000     1.405841    3.214737
                               NM  |   .7351664   .4491932     1.64   0.102    -.1452362    1.615569
                               NY  |   3.641282   .5404213     6.74   0.000     2.582076    4.700489
                               NC  |   1.346601   .4209152     3.20   0.001     .5216225     2.17158
                               ND  |  -1.551076     .46261    -3.35   0.001    -2.457775   -.6443774
                               OH  |   1.919857   .4322814     4.44   0.000     1.072601    2.767113
                               OK  |    .683663   .4261656     1.60   0.109    -.1516063    1.518932
                               OR  |   .1940121   .4505454     0.43   0.667    -.6890406    1.077065
                               PA  |   2.779193   .4716738     5.89   0.000     1.854729    3.703657
                               RI  |  -.5832128   .4542747    -1.28   0.199    -1.473575    .3071492
                               SC  |   .0041058   .4605279     0.01   0.993    -.8985124     .906724
                               SD  |  -.8806204   .4824892    -1.83   0.068    -1.826282    .0650409
                               TN  |   1.640084   .4494602     3.65   0.000     .7591582     2.52101
                               TX  |   2.353619    .426333     5.52   0.000     1.518022    3.189217
                               UT  |  -.8704456   .4460617    -1.95   0.051     -1.74471    .0038192
                               VT  |  -.5412116   .4771942    -1.13   0.257    -1.476495    .3940718
                               VA  |   1.161061   .4532328     2.56   0.010     .2727409    2.049381
                               WA  |   1.941871   .4429381     4.38   0.000     1.073729    2.810014
                               WV  |   .3810034   .4625073     0.82   0.410    -.5254942    1.287501
                               WI  |   .6908759   .4255377     1.62   0.104    -.1431625    1.524914
                               WY  |   -2.42171   .5767789    -4.20   0.000    -3.552176   -1.291245
                                   |
                              year |
                             1978  |   1.149918   .1800814     6.39   0.000     .7969646    1.502871
                             1984  |   .9733902   .1818436     5.35   0.000     .6169833    1.329797
                             1988  |    1.42995   .1689554     8.46   0.000     1.098804    1.761097
                             1994  |   1.580496   .1817795     8.69   0.000     1.224215    1.936777
                             1998  |   1.903539   .1887352    10.09   0.000     1.533625    2.273453
                             2004  |   1.903018   .1931394     9.85   0.000     1.524472    2.281564
                             2008  |   2.085419   .2019928    10.32   0.000      1.68952    2.481317
                                   |
                             _cons |   2.478219   1.141088     2.17   0.030     .2417289     4.71471
-----------------------------------+----------------------------------------------------------------
Less_than_Monthly                  |
                      intersection |
                      White Woman  |  -.0388994   .0994852    -0.39   0.696    -.2338869     .156088
                     Man of Color  |   .2019461   .1477076     1.37   0.172    -.0875556    .4914477
                   Woman of Color  |   .4383769   .2603034     1.68   0.092    -.0718084    .9485622
                                   |
                     civil_service |
                              Yes  |   .6400069   .0883879     7.24   0.000     .4667698     .813244
                      weekly_hours |  -.0314123   .0043435    -7.23   0.000    -.0399254   -.0228992
                               age |   .0483952   .0330163     1.47   0.143    -.0163154    .1131059
                             age_2 |  -.0006134   .0003311    -1.85   0.064    -.0012622    .0000355
                                   |
                               edu |
              High school or less  |  -.0401431   .2806391    -0.14   0.886    -.5901856    .5098994
                     Some college  |  -.2718719   .1496237    -1.82   0.069    -.5651289    .0213852
                   Graduate study  |  -.0162722   .1142505    -0.14   0.887    -.2401991    .2076547
                  Graduate degree  |   .0380392   .0943878     0.40   0.687    -.1469574    .2230358
                                   |
                years_employ_state |  -.0024935   .0056548    -0.44   0.659    -.0135768    .0085898
               years_employ_agency |   .0332213   .0061663     5.39   0.000     .0211356    .0453071
             years_employ_position |  -.0020784   .0080317    -0.26   0.796    -.0178201    .0136634
                                   |
                              pid5 |
                       Republican  |  -.4819933   .1185991    -4.06   0.000    -.7144433   -.2495432
                  Lean Republican  |  -.2438247   .1510485    -1.61   0.106    -.5398744     .052225
                  Lean Democratic  |   .1011362   .1479952     0.68   0.494    -.1889291    .3912015
                       Democratic  |  -.2800854   .1120539    -2.50   0.012     -.499707   -.0604638
                                   |
                       agency_size |
                           25-100  |  -.1000498   .1082066    -0.92   0.355    -.3121309    .1120313
                          101-500  |  -.4114489   .1216932    -3.38   0.001    -.6499632   -.1729347
                        501-1,000  |  -.7114778    .158379    -4.49   0.000    -1.021895   -.4010607
                      1,001-5,000  |   -1.08339   .1666576    -6.50   0.000    -1.410033   -.7567471
                       Over 5,000  |  -1.157907   .2298351    -5.04   0.000    -1.608376   -.7074388
                                   |
                 log_agency_budget |  -.1281339   .0291968    -4.39   0.000    -.1853587   -.0709092
                      inst6017_nom |  -.0024861   .0040019    -0.62   0.534    -.0103298    .0053575
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.0088236   .2156718    -0.04   0.967    -.4315326    .4138853
                Staff: Non-Fiscal  |   .4852139   .2155781     2.25   0.024     .0626886    .9077393
Income Security & Social Services  |   1.240465   .1987329     6.24   0.000     .8509554    1.629974
                        Education  |   .4398808   .2106788     2.09   0.037     .0269579    .8528037
                           Health  |   1.179091   .2121137     5.56   0.000     .7633555    1.594826
                Natural Resources  |   .4362216   .1782595     2.45   0.014     .0868395    .7856038
             Environment & Energy  |   .3715131   .1895467     1.96   0.050     8.51e-06    .7430177
             Economic Development  |   .0955989   .1948028     0.49   0.624    -.2862075    .4774054
                 Criminal Justice  |   .5391147   .1876555     2.87   0.004     .1713168    .9069127
                       Regulatory  |   .6697386   .1810033     3.70   0.000     .3149787    1.024498
                   Transportation  |   .7421037    .210647     3.52   0.000     .3292431    1.154964
                            Other  |   .5685833   .1875867     3.03   0.002     .2009201    .9362465
                                   |
                             state |
                               AK  |    .612471   .3442717     1.78   0.075    -.0622891    1.287231
                               AZ  |   .1440291   .3324635     0.43   0.665    -.5075874    .7956455
                               AR  |  -.2288979   .3118687    -0.73   0.463    -.8401494    .3823536
                               CA  |   1.633596   .3766613     4.34   0.000     .8953537    2.371839
                               CO  |   .0118171   .3206619     0.04   0.971    -.6166687    .6403029
                               CT  |   .4216248   .3706552     1.14   0.255    -.3048461    1.148096
                               DE  |   .4991704   .3256268     1.53   0.125    -.1390463    1.137387
                               FL  |   .9098407   .3440843     2.64   0.008     .2354478    1.584234
                               GA  |   .3628488   .3313182     1.10   0.273    -.2865229     1.01222
                               HI  |   .3585305   .3710867     0.97   0.334     -.368786    1.085847
                               ID  |   -.486626   .3103069    -1.57   0.117    -1.094816    .1215644
                               IL  |   .5851486   .3476523     1.68   0.092    -.0962374    1.266535
                               IN  |   .3278995   .3349146     0.98   0.328     -.328521      .98432
                               IA  |   .2000016   .3100888     0.64   0.519    -.4077614    .8077645
                               KS  |  -.0861223   .3194671    -0.27   0.787    -.7122663    .5400217
                               KY  |   .2212686   .3526146     0.63   0.530    -.4698434    .9123806
                               LA  |   .4644334   .3664496     1.27   0.205    -.2537945    1.182661
                               ME  |   .4403311   .3517355     1.25   0.211    -.2490578     1.12972
                               MD  |   1.122136    .362929     3.09   0.002     .4108083    1.833464
                               MA  |    .774831   .3506548     2.21   0.027     .0875602    1.462102
                               MI  |  -.0517681   .3200797    -0.16   0.872    -.6791128    .5755766
                               MN  |   .5452108   .3275482     1.66   0.096    -.0967717    1.187193
                               MS  |  -.1314021   .3207814    -0.41   0.682    -.7601221    .4973179
                               MO  |   .7490788   .3222146     2.32   0.020     .1175498    1.380608
                               MT  |  -.4829927   .3064281    -1.58   0.115    -1.083581    .1175953
                               NE  |  -.2135503   .3223721    -0.66   0.508     -.845388    .4182874
                               NV  |    .076727    .319338     0.24   0.810     -.549164    .7026181
                               NH  |   .0158065   .3313754     0.05   0.962    -.6336774    .6652905
                               NJ  |    1.18448   .3664089     3.23   0.001     .4663316    1.902628
                               NM  |   .1009628   .3513687     0.29   0.774    -.5877072    .7896329
                               NY  |   1.971201   .4628268     4.26   0.000     1.064077    2.878324
                               NC  |   .8661243   .3105428     2.79   0.005     .2574715    1.474777
                               ND  |  -.7659508   .3134475    -2.44   0.015    -1.380297   -.1516051
                               OH  |   .8136352   .3360065     2.42   0.015     .1550746    1.472196
                               OK  |   .0123227   .3162633     0.04   0.969     -.607542    .6321875
                               OR  |    .055744   .3144723     0.18   0.859    -.5606104    .6720984
                               PA  |   1.651749   .3654891     4.52   0.000     .9354033    2.368094
                               RI  |  -.1824874   .3428581    -0.53   0.595    -.8544769    .4895022
                               SC  |  -.1471693   .3264958    -0.45   0.652    -.7870893    .4927507
                               SD  |  -.0808122   .3161028    -0.26   0.798    -.7003624     .538738
                               TN  |   .6495643   .3424339     1.90   0.058    -.0215939    1.320723
                               TX  |   1.055811   .3467748     3.04   0.002     .3761447    1.735477
                               UT  |  -.2168819   .2993477    -0.72   0.469    -.8035927    .3698288
                               VT  |  -.0991664   .3240467    -0.31   0.760    -.7342863    .5359534
                               VA  |   .5748582   .3447764     1.67   0.095    -.1008911    1.250608
                               WA  |   .8215228   .3385032     2.43   0.015     .1580688    1.484977
                               WV  |   .6048694   .3368352     1.80   0.073    -.0553155    1.265054
                               WI  |   .1105757   .3246141     0.34   0.733    -.5256563    .7468077
                               WY  |  -.6821402   .3001246    -2.27   0.023    -1.270374   -.0939068
                                   |
                              year |
                             1978  |   .3901277   .1261551     3.09   0.002     .1428684    .6373871
                             1984  |   .3177924   .1237453     2.57   0.010     .0752561    .5603287
                             1988  |   .4559757   .1159624     3.93   0.000     .2286935    .6832579
                             1994  |   .5328839   .1263405     4.22   0.000      .285261    .7805068
                             1998  |   .6373587    .135842     4.69   0.000     .3711131    .9036042
                             2004  |    .433114   .1387255     3.12   0.002      .161217     .705011
                             2008  |  -.2279927   .1627509    -1.40   0.161    -.5469785    .0909931
                                   |
                             _cons |   1.083983   .8926209     1.21   0.225    -.6655219    2.833488
-----------------------------------+----------------------------------------------------------------
Monthly                            |  (base outcome)
-----------------------------------+----------------------------------------------------------------
Weekly                             |
                      intersection |
                      White Woman  |  -.3716392   .1320008    -2.82   0.005     -.630356   -.1129224
                     Man of Color  |  -.2452264   .1876599    -1.31   0.191     -.613033    .1225803
                   Woman of Color  |  -.6875859    .358051    -1.92   0.055    -1.389353    .0141811
                                   |
                     civil_service |
                              Yes  |  -.4218687   .1356534    -3.11   0.002    -.6877445   -.1559928
                      weekly_hours |   .0410726   .0053229     7.72   0.000     .0306399    .0515053
                               age |  -.0644773   .0362867    -1.78   0.076     -.135598    .0066434
                             age_2 |   .0006918   .0003561     1.94   0.052    -6.08e-06    .0013896
                                   |
                               edu |
              High school or less  |   .3343451   .3185095     1.05   0.294    -.2899221    .9586124
                     Some college  |  -.2640586   .1833676    -1.44   0.150    -.6234525    .0953353
                   Graduate study  |  -.0276355   .1387805    -0.20   0.842    -.2996402    .2443693
                  Graduate degree  |  -.1806261   .1155237    -1.56   0.118    -.4070484    .0457962
                                   |
                years_employ_state |   .0060925   .0066747     0.91   0.361    -.0069898    .0191747
               years_employ_agency |  -.0132777   .0076364    -1.74   0.082    -.0282447    .0016893
             years_employ_position |  -.0010828   .0104956    -0.10   0.918    -.0216539    .0194882
                                   |
                              pid5 |
                       Republican  |   .1147139   .1537436     0.75   0.456    -.1866179    .4160458
                  Lean Republican  |  -.1671163   .2044433    -0.82   0.414    -.5678179    .2335852
                  Lean Democratic  |  -.0890623   .2094407    -0.43   0.671    -.4995584    .3214339
                       Democratic  |   .2424282   .1458094     1.66   0.096     -.043353    .5282093
                                   |
                       agency_size |
                           25-100  |   .0594134   .1520172     0.39   0.696    -.2385349    .3573616
                          101-500  |   .2280393   .1648456     1.38   0.167    -.0950522    .5511307
                        501-1,000  |   .2351568   .2060086     1.14   0.254    -.1686127    .6389263
                      1,001-5,000  |   .4182718    .212254     1.97   0.049     .0022616     .834282
                       Over 5,000  |   .7681327   .2744344     2.80   0.005     .2302511    1.306014
                                   |
                 log_agency_budget |   .0906286   .0356559     2.54   0.011     .0207443    .1605128
                      inst6017_nom |  -.0098404   .0049839    -1.97   0.048    -.0196087   -.0000721
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .4766949   .2204217     2.16   0.031     .0446763    .9087134
                Staff: Non-Fiscal  |   .2388843   .2329733     1.03   0.305    -.2177349    .6955036
Income Security & Social Services  |  -.8614265   .2330198    -3.70   0.000    -1.318137   -.4047161
                        Education  |  -.9598654   .2495254    -3.85   0.000    -1.448926   -.4708046
                           Health  |  -1.158243    .260944    -4.44   0.000    -1.669684   -.6468021
                Natural Resources  |  -.7535785   .2059549    -3.66   0.000    -1.157243   -.3499143
             Environment & Energy  |  -.6278228   .2314797    -2.71   0.007    -1.081515   -.1741309
             Economic Development  |  -.1003131   .2072102    -0.48   0.628    -.5064375    .3058114
                 Criminal Justice  |  -.9927901    .220847    -4.50   0.000    -1.425642   -.5599379
                       Regulatory  |  -.8773276   .2259342    -3.88   0.000     -1.32015   -.4345047
                   Transportation  |   -1.06811   .2414851    -4.42   0.000    -1.541412   -.5948079
                            Other  |  -.5395496   .2241573    -2.41   0.016    -.9788899   -.1002094
                                   |
                             state |
                               AK  |    .069555   .3824629     0.18   0.856    -.6800585    .8191685
                               AZ  |  -1.157887    .417571    -2.77   0.006    -1.976311   -.3394632
                               AR  |  -.7135313   .3833463    -1.86   0.063    -1.464876    .0378136
                               CA  |  -1.421574   .5113343    -2.78   0.005    -2.423771   -.4193772
                               CO  |  -.0984664   .3740694    -0.26   0.792     -.831629    .6346963
                               CT  |  -1.499354   .5199319    -2.88   0.004    -2.518402   -.4803065
                               DE  |  -.4002769   .4062555    -0.99   0.324    -1.196523    .3959691
                               FL  |  -1.053926   .4423963    -2.38   0.017    -1.921007    -.186845
                               GA  |  -.8996593   .3988157    -2.26   0.024    -1.681324   -.1179949
                               HI  |  -.2375518   .4362073    -0.54   0.586    -1.092502    .6173988
                               ID  |   -.385186   .3638684    -1.06   0.290    -1.098355    .3279829
                               IL  |  -1.652939   .5325384    -3.10   0.002    -2.696695   -.6091824
                               IN  |  -.3368299   .3914262    -0.86   0.390    -1.104011    .4303514
                               IA  |  -.7176237   .3768405    -1.90   0.057    -1.456218    .0209702
                               KS  |  -.8740576   .4013491    -2.18   0.029    -1.660687   -.0874279
                               KY  |   -.817354   .3961128    -2.06   0.039    -1.593721   -.0409871
                               LA  |  -.3642935   .4247055    -0.86   0.391    -1.196701     .468114
                               ME  |   .0618784    .414451     0.15   0.881    -.7504307    .8741875
                               MD  |   .3441444   .3995698     0.86   0.389    -.4389981    1.127287
                               MA  |  -1.315265   .4970835    -2.65   0.008    -2.289531   -.3409998
                               MI  |  -1.144568   .4113355    -2.78   0.005    -1.950771   -.3383651
                               MN  |  -1.525916   .4373098    -3.49   0.000    -2.383027   -.6688046
                               MS  |   -.629905   .3954236    -1.59   0.111    -1.404921    .1451111
                               MO  |  -1.325873   .4381159    -3.03   0.002    -2.184564   -.4671816
                               MT  |  -.3983325   .3468159    -1.15   0.251    -1.078079    .2814142
                               NE  |   .1604617   .3716013     0.43   0.666    -.5678634    .8887868
                               NV  |  -.4693992   .3789902    -1.24   0.216    -1.212206    .2734078
                               NH  |  -.2652966   .3880918    -0.68   0.494    -1.025943    .4953494
                               NJ  |  -.1474391   .4310492    -0.34   0.732      -.99228    .6974018
                               NM  |   .6062822   .3843854     1.58   0.115    -.1470993    1.359664
                               NY  |  -.6452331   .5763921    -1.12   0.263    -1.774941    .4844746
                               NC  |  -.5475869   .3652997    -1.50   0.134    -1.263561    .1683874
                               ND  |  -.0963659   .3561433    -0.27   0.787     -.794394    .6016621
                               OH  |  -.5532244   .4074794    -1.36   0.175    -1.351869    .2454206
                               OK  |  -.9284137   .3693595    -2.51   0.012    -1.652345   -.2044824
                               OR  |  -.5314292   .3757836    -1.41   0.157    -1.267952    .2050932
                               PA  |  -.9871748   .4593204    -2.15   0.032    -1.887426   -.0869234
                               RI  |  -.0941802   .4177883    -0.23   0.822    -.9130302    .7246698
                               SC  |  -1.362108   .4061017    -3.35   0.001    -2.158053   -.5661636
                               SD  |   .0524885   .3637892     0.14   0.885    -.6605252    .7655022
                               TN  |  -.6782705   .4209789    -1.61   0.107    -1.503374     .146833
                               TX  |  -2.326039   .6416308    -3.63   0.000    -3.583612   -1.068465
                               UT  |  -.6387661    .364005    -1.75   0.079    -1.352203    .0746706
                               VT  |  -.0178172   .3670398    -0.05   0.961     -.737202    .7015676
                               VA  |  -1.227792   .4614215    -2.66   0.008    -2.132161    -.323422
                               WA  |   .0381416   .3888645     0.10   0.922    -.7240188    .8003021
                               WV  |  -.3321057   .4001904    -0.83   0.407    -1.116464     .452253
                               WI  |  -.1798169   .3650726    -0.49   0.622    -.8953461    .5357123
                               WY  |  -.4209824   .3488692    -1.21   0.228    -1.104753    .2627888
                                   |
                              year |
                             1978  |  -.3588219   .1503951    -2.39   0.017    -.6535909   -.0640529
                             1984  |  -.3768351    .148332    -2.54   0.011    -.6675604   -.0861097
                             1988  |  -.7052511   .1406272    -5.02   0.000    -.9808754   -.4296268
                             1994  |  -.2103269   .1489571    -1.41   0.158    -.5022774    .0816236
                             1998  |  -.5869241   .1635265    -3.59   0.000    -.9074301   -.2664181
                             2004  |  -.9020768   .1776028    -5.08   0.000    -1.250172   -.5539818
                             2008  |  -1.433583   .2017277    -7.11   0.000    -1.828962   -1.038204
                                   |
                             _cons |   .4494499   1.026747     0.44   0.662    -1.562938    2.461838
-----------------------------------+----------------------------------------------------------------
Daily                              |
                      intersection |
                      White Woman  |  -.4453364   .3086913    -1.44   0.149     -1.05036    .1596875
                     Man of Color  |   .1726202    .420971     0.41   0.682    -.6524678    .9977082
                   Woman of Color  |  -1.137752   1.048616    -1.09   0.278    -3.193002    .9174973
                                   |
                     civil_service |
                              Yes  |  -.4207819   .3101043    -1.36   0.175    -1.028575    .1870113
                      weekly_hours |   .0719213   .0119631     6.01   0.000     .0484741    .0953685
                               age |  -.1783643   .0726907    -2.45   0.014    -.3208354   -.0358932
                             age_2 |   .0017237   .0007421     2.32   0.020     .0002692    .0031782
                                   |
                               edu |
              High school or less  |  -.3083416   .8708979    -0.35   0.723     -2.01527    1.398587
                     Some college  |   -.516355    .403122    -1.28   0.200     -1.30646    .2737496
                   Graduate study  |  -.1811094   .2758493    -0.66   0.511    -.7217641    .3595452
                  Graduate degree  |  -.1475484   .2347393    -0.63   0.530    -.6076289    .3125322
                                   |
                years_employ_state |   .0056019   .0157297     0.36   0.722    -.0252278    .0364315
               years_employ_agency |  -.0280849   .0197747    -1.42   0.156    -.0668427    .0106728
             years_employ_position |  -.0305198   .0288266    -1.06   0.290    -.0870189    .0259794
                                   |
                              pid5 |
                       Republican  |   .1894951   .3142813     0.60   0.547    -.4264849    .8054751
                  Lean Republican  |  -.6846603   .5225133    -1.31   0.190    -1.708768     .339447
                  Lean Democratic  |   -.560292   .4999967    -1.12   0.262    -1.540268    .4196836
                       Democratic  |   .2477556   .3114299     0.80   0.426    -.3626357    .8581469
                                   |
                       agency_size |
                           25-100  |  -.4229791   .2791844    -1.52   0.130    -.9701705    .1242123
                          101-500  |  -.4934863   .3200804    -1.54   0.123    -1.120832    .1338596
                        501-1,000  |  -.5038897   .4641709    -1.09   0.278    -1.413648    .4058686
                      1,001-5,000  |  -.4570951   .4747103    -0.96   0.336     -1.38751    .4733201
                       Over 5,000  |   .7207548   .6237444     1.16   0.248    -.5017617    1.943271
                                   |
                 log_agency_budget |   .1258505   .0897149     1.40   0.161    -.0499875    .3016885
                      inst6017_nom |   -.023691   .0108669    -2.18   0.029    -.0449897   -.0023923
                                   |
                          funcat13 |
                    Staff: Fiscal  |   2.216571   .4207119     5.27   0.000     1.391991    3.041151
                Staff: Non-Fiscal  |   1.197124   .4541876     2.64   0.008     .3069326    2.087315
Income Security & Social Services  |  -1.566817   .6428166    -2.44   0.015    -2.826715   -.3069201
                        Education  |  -2.969313   1.122104    -2.65   0.008    -5.168597   -.7700292
                           Health  |   -1.83176   .7558258    -2.42   0.015    -3.313151   -.3503684
                Natural Resources  |  -.7645165   .5117477    -1.49   0.135    -1.767524    .2384905
             Environment & Energy  |  -.5012342   .5476454    -0.92   0.360    -1.574599     .572131
             Economic Development  |    .396285   .4469664     0.89   0.375     -.479753    1.272323
                 Criminal Justice  |  -.9651753   .5291804    -1.82   0.068     -2.00235    .0719992
                       Regulatory  |  -.8348554   .5463528    -1.53   0.126    -1.905687    .2359764
                   Transportation  |  -.3418661   .4908233    -0.70   0.486    -1.303862    .6201299
                            Other  |  -.9636625   .6235954    -1.55   0.122    -2.185887    .2585621
                                   |
                             state |
                               AK  |  -.2563691    .664114    -0.39   0.699    -1.558009    1.045271
                               AZ  |  -1.415293   .7252933    -1.95   0.051    -2.836841     .006256
                               AR  |  -1.642083   .8344692    -1.97   0.049    -3.277613   -.0065536
                               CA  |  -15.68471   .6183479   -25.37   0.000    -16.89665   -14.47277
                               CO  |  -1.269837   .7508812    -1.69   0.091    -2.741537    .2018637
                               CT  |  -2.007595    1.13685    -1.77   0.077    -4.235779    .2205901
                               DE  |  -.8678408   .7323879    -1.18   0.236    -2.303295    .5676132
                               FL  |   -1.71494   .7959828    -2.15   0.031    -3.275037   -.1548422
                               GA  |  -2.753591   1.239804    -2.22   0.026    -5.183562   -.3236199
                               HI  |  -1.147181   .9594163    -1.20   0.232    -3.027603    .7332399
                               ID  |  -1.239464   .6910944    -1.79   0.073    -2.593984    .1150566
                               IL  |  -2.059695   .7639437    -2.70   0.007    -3.556997   -.5623931
                               IN  |  -.7862681   .6830901    -1.15   0.250      -2.1251    .5525639
                               IA  |  -1.643259   .6800191    -2.42   0.016    -2.976072   -.3104462
                               KS  |   -.692504   .6446181    -1.07   0.283    -1.955932    .5709243
                               KY  |  -1.990681   .9235834    -2.16   0.031    -3.800871   -.1804904
                               LA  |  -.4632899   .7420885    -0.62   0.532    -1.917757    .9911768
                               ME  |  -.3924494   .7437276    -0.53   0.598    -1.850129     1.06523
                               MD  |  -.8620669   .8080914    -1.07   0.286    -2.445897    .7217632
                               MA  |  -2.384433   1.217177    -1.96   0.050    -4.770056    .0011901
                               MI  |   -2.37037    .876813    -2.70   0.007    -4.088892   -.6518483
                               MN  |  -1.931637   .8018058    -2.41   0.016    -3.503147   -.3601265
                               MS  |  -.4615594   .7088479    -0.65   0.515    -1.850876    .9277569
                               MO  |  -1.952724   .8894121    -2.20   0.028    -3.695939   -.2095079
                               MT  |  -2.727307   1.133855    -2.41   0.016    -4.949622   -.5049914
                               NE  |  -.0185242   .6079096    -0.03   0.976    -1.210005    1.172957
                               NV  |  -1.517089   .9456454    -1.60   0.109     -3.37052    .3363421
                               NH  |   -1.21162   .7934683    -1.53   0.127    -2.766789    .3435491
                               NJ  |  -1.302475   .8721302    -1.49   0.135    -3.011818    .4068691
                               NM  |   .0861043   .7105637     0.12   0.904    -1.306575    1.478783
                               NY  |  -.7009175   .8914483    -0.79   0.432    -2.448124    1.046289
                               NC  |  -2.900338   1.188922    -2.44   0.015    -5.230582   -.5700946
                               ND  |  -1.288064   .7494789    -1.72   0.086    -2.757016    .1808874
                               OH  |  -1.401822   .7391586    -1.90   0.058    -2.850546    .0469026
                               OK  |   -1.73298   .7969994    -2.17   0.030     -3.29507   -.1708898
                               OR  |  -.4217949   .6920439    -0.61   0.542    -1.778176    .9345863
                               PA  |  -2.343784    1.25891    -1.86   0.063    -4.811201    .1236339
                               RI  |  -.0474308   .7713497    -0.06   0.951    -1.559248    1.464387
                               SC  |   -2.88836   1.105574    -2.61   0.009    -5.055245   -.7214755
                               SD  |  -.7609939   .6566848    -1.16   0.247    -2.048073    .5260848
                               TN  |  -2.093573   1.201489    -1.74   0.081    -4.448449     .261303
                               TX  |  -15.95797    .644846   -24.75   0.000    -17.22184   -14.69409
                               UT  |  -1.153461   .6914366    -1.67   0.095    -2.508652    .2017302
                               VT  |   -.444322    .655808    -0.68   0.498    -1.729682     .841038
                               VA  |  -1.720682   .8071324    -2.13   0.033    -3.302633   -.1387315
                               WA  |  -1.563769   .9453646    -1.65   0.098    -3.416649    .2891117
                               WV  |   -1.39487   .7783208    -1.79   0.073    -2.920351    .1306104
                               WI  |  -.9031233   .7342733    -1.23   0.219    -2.342273     .536026
                               WY  |  -1.452054    .732149    -1.98   0.047     -2.88704   -.0170683
                                   |
                              year |
                             1978  |  -.5515931   .2577194    -2.14   0.032    -1.056714   -.0464724
                             1984  |  -2.161931   .4202187    -5.14   0.000    -2.985544   -1.338317
                             1988  |  -1.591678   .3059685    -5.20   0.000    -2.191365   -.9919909
                             1994  |  -.9222488   .2967571    -3.11   0.002    -1.503882   -.3406156
                             1998  |  -1.759795   .3953989    -4.45   0.000    -2.534763   -.9848278
                             2004  |  -2.186498   .4719037    -4.63   0.000    -3.111412   -1.261583
                             2008  |  -1.978554   .4685402    -4.22   0.000    -2.896876   -1.060232
                                   |
                             _cons |   2.024791   1.948915     1.04   0.299    -1.795013    5.844595
----------------------------------------------------------------------------------------------------

. est sto mlogit1

. 
.  esttab mlogit1 using Table_B8.rtf  ,starlevels(+ 0.10 * 0.05 ** 0.01) cells(b(star fmt(3)) se(par fmt(3)))
>  ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Gov." ) 
(output written to Table_B8.rtf)

. 
. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B9 ******
. mlogit reve_1b i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r, base(3)  r 

Iteration 0:   log pseudolikelihood = -9204.7672  
Iteration 1:   log pseudolikelihood = -8030.5699  
Iteration 2:   log pseudolikelihood = -7821.7995  
Iteration 3:   log pseudolikelihood = -7810.6032  
Iteration 4:   log pseudolikelihood = -7809.7982  
Iteration 5:   log pseudolikelihood = -7809.6385  
Iteration 6:   log pseudolikelihood = -7809.6046  
Iteration 7:   log pseudolikelihood = -7809.5976  
Iteration 8:   log pseudolikelihood =  -7809.596  
Iteration 9:   log pseudolikelihood = -7809.5956  
Iteration 10:  log pseudolikelihood = -7809.5955  
Iteration 11:  log pseudolikelihood = -7809.5955  

Multinomial logistic regression                 Number of obs     =      6,378
                                                Wald chi2(368)    =   16660.31
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -7809.5955               Pseudo R2         =     0.1516

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1b |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
Never                              |
                      intersection |
                      White Woman  |  -.0857157   .2699418    -0.32   0.751    -.6147919    .4433605
                     Man of Color  |   .1797136    .346097     0.52   0.604    -.4986242    .8580513
                   Woman of Color  |   .1010158    .604455     0.17   0.867    -1.083694    1.285726
                                   |
                     civil_service |
                              Yes  |    .811709   .1982454     4.09   0.000     .4231553    1.200263
                      weekly_hours |  -.0476154   .0118659    -4.01   0.000    -.0708722   -.0243585
                               age |   .0157206   .0747323     0.21   0.833    -.1307519    .1621932
                             age_2 |  -.0001114   .0007417    -0.15   0.881    -.0015651    .0013422
                                   |
                               edu |
              High school or less  |   1.159089   .7087881     1.64   0.102    -.2301102    2.548288
                     Some college  |   .1752862   .4240667     0.41   0.679    -.6558692    1.006442
                   Graduate study  |   -.336702   .3095652    -1.09   0.277    -.9434387    .2700346
                  Graduate degree  |  -.2777039    .239173    -1.16   0.246    -.7464743    .1910665
                                   |
                years_employ_state |  -.0505908   .0194802    -2.60   0.009    -.0887713   -.0124103
               years_employ_agency |   .0620319   .0199242     3.11   0.002     .0229812    .1010826
             years_employ_position |   -.005226   .0202245    -0.26   0.796    -.0448652    .0344133
                                   |
                              pid5 |
                       Republican  |  -.4923983   .2994213    -1.64   0.100    -1.079253    .0944566
                  Lean Republican  |   .1403664   .3629228     0.39   0.699    -.5709492    .8516821
                  Lean Democratic  |  -.2615781   .3691139    -0.71   0.479     -.985028    .4618718
                       Democratic  |  -.2596034   .2793479    -0.93   0.353    -.8071152    .2879085
                                   |
                       agency_size |
                           25-100  |  -.5939214   .2483429    -2.39   0.017    -1.080665   -.1071783
                          101-500  |  -.8142913   .3213799    -2.53   0.011    -1.444184   -.1843983
                        501-1,000  |  -.8468056   .4891548    -1.73   0.083    -1.805531    .1119202
                      1,001-5,000  |  -1.176214     .62036    -1.90   0.058    -2.392097    .0396694
                       Over 5,000  |   .0078937   .6940276     0.01   0.991    -1.352375    1.368163
                                   |
                 log_agency_budget |  -.1875544   .0887986    -2.11   0.035    -.3615965   -.0135123
                      inst6017_nom |  -.0031469   .0111874    -0.28   0.778    -.0250737      .01878
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -2.106653   1.161592    -1.81   0.070    -4.383331    .1700258
                Staff: Non-Fiscal  |  -.6588332   .6169918    -1.07   0.286    -1.868115    .5504485
Income Security & Social Services  |  -.4182827   .5323308    -0.79   0.432    -1.461632    .6250665
                        Education  |  -.6223307   .6044072    -1.03   0.303    -1.806947    .5622856
                           Health  |    -.45967   .5491909    -0.84   0.403    -1.536064    .6167244
                Natural Resources  |  -.2970751   .4453889    -0.67   0.505    -1.170021    .5758711
             Environment & Energy  |  -.4446946   .4610838    -0.96   0.335    -1.348402     .459013
             Economic Development  |  -2.776281   1.055955    -2.63   0.009    -4.845915   -.7066475
                 Criminal Justice  |  -.8020318   .5264236    -1.52   0.128    -1.833803    .2297395
                       Regulatory  |  -.1276655   .4385152    -0.29   0.771    -.9871395    .7318085
                   Transportation  |  -.7682713   .5909749    -1.30   0.194    -1.926561    .3900182
                            Other  |  -.6774298   .4832091    -1.40   0.161    -1.624502    .2696427
                                   |
                             state |
                               AK  |   .2146902   .9346493     0.23   0.818    -1.617189    2.046569
                               AZ  |   .4338912    .936551     0.46   0.643    -1.401715    2.269497
                               AR  |   .9271852    1.03614     0.89   0.371    -1.103612    2.957983
                               CA  |   1.181497   .9684335     1.22   0.222    -.7165977    3.079592
                               CO  |  -.8369434   1.114164    -0.75   0.453    -3.020665    1.346778
                               CT  |   1.842935   .8720127     2.11   0.035     .1338216    3.552049
                               DE  |  -.1570743    1.03712    -0.15   0.880    -2.189792    1.875644
                               FL  |   .5884685   1.006502     0.58   0.559    -1.384239    2.561176
                               GA  |   1.135689   .8648021     1.31   0.189     -.559292     2.83067
                               HI  |   2.190276   .7985239     2.74   0.006     .6251975    3.755354
                               ID  |  -14.89187   .7092529   -21.00   0.000    -16.28198   -13.50176
                               IL  |   1.633675   .9766072     1.67   0.094    -.2804398     3.54779
                               IN  |  -.6525003    1.15922    -0.56   0.574     -2.92453     1.61953
                               IA  |  -.2573864   .9808553    -0.26   0.793    -2.179828    1.665055
                               KS  |   .1403534   .8748638     0.16   0.873    -1.574348    1.855055
                               KY  |   .6860951   .8779818     0.78   0.435    -1.034718    2.406908
                               LA  |   1.253527   .8794664     1.43   0.154    -.4701951     2.97725
                               ME  |  -15.21855   .7071139   -21.52   0.000    -16.60447   -13.83263
                               MD  |   .8095045   .8819696     0.92   0.359    -.9191241    2.538133
                               MA  |   1.414556   .9215768     1.53   0.125    -.3917018    3.220813
                               MI  |   .6757982   .8924252     0.76   0.449    -1.073323    2.424919
                               MN  |   1.007218    .781905     1.29   0.198    -.5252873    2.539724
                               MS  |   1.305738    .787952     1.66   0.097    -.2386199    2.850095
                               MO  |   1.721266   .7607463     2.26   0.024     .2302307    3.212301
                               MT  |  -.8319496    .987555    -0.84   0.400    -2.767522    1.103623
                               NE  |  -.6061285   1.203756    -0.50   0.615    -2.965448    1.753191
                               NV  |   .1520696   .9085082     0.17   0.867    -1.628574    1.932713
                               NH  |  -.8562464   1.167826    -0.73   0.463    -3.145144    1.432651
                               NJ  |   .5147159   .9978036     0.52   0.606    -1.440943    2.470375
                               NM  |  -14.74013   .7132715   -20.67   0.000    -16.13811   -13.34214
                               NY  |  -13.77695   .7688608   -17.92   0.000    -15.28389   -12.27001
                               NC  |   .3365406   .8452267     0.40   0.691    -1.320073    1.993154
                               ND  |  -1.251354   1.204062    -1.04   0.299    -3.611271    1.108564
                               OH  |   1.499918   .8874813     1.69   0.091    -.2395139    3.239349
                               OK  |   1.226861   .7900504     1.55   0.120    -.3216096    2.775331
                               OR  |  -.8080823   1.227974    -0.66   0.510    -3.214868    1.598703
                               PA  |   1.330151   .8736431     1.52   0.128    -.3821581     3.04246
                               RI  |   .7204494    .831431     0.87   0.386    -.9091255    2.350024
                               SC  |   .2309854   .8997207     0.26   0.797    -1.532435    1.994406
                               SD  |  -.5467399   1.024014    -0.53   0.593    -2.553771    1.460291
                               TN  |   .6898202    .829039     0.83   0.405    -.9350663    2.314707
                               TX  |   .4374393   .9613986     0.46   0.649    -1.446867    2.321746
                               UT  |   -.351717   .8804048    -0.40   0.690    -2.077279    1.373845
                               VT  |  -.5553559   1.256028    -0.44   0.658    -3.017126    1.906414
                               VA  |   1.294395   .8369471     1.55   0.122    -.3459907    2.934782
                               WA  |  -.4626867   1.229589    -0.38   0.707    -2.872637    1.947264
                               WV  |   1.466679   .7908045     1.85   0.064    -.0832689    3.016628
                               WI  |    .702081   .8728576     0.80   0.421    -1.008689     2.41285
                               WY  |  -1.188494    1.22844    -0.97   0.333    -3.596192    1.219203
                                   |
                              year |
                             1984  |  -.7794091   .3685785    -2.11   0.034     -1.50181   -.0570086
                             1988  |  -.8833353   .3523209    -2.51   0.012    -1.573872    -.192799
                             1994  |  -.3853601   .3412914    -1.13   0.259    -1.054279    .2835587
                             1998  |  -.2971395    .351798    -0.84   0.398    -.9866509    .3923718
                             2004  |  -.0661732   .3679688    -0.18   0.857    -.7873787    .6550323
                             2008  |   1.049514   .3648391     2.88   0.004     .3344426    1.764586
                                   |
                             _cons |   1.078751   2.079427     0.52   0.604     -2.99685    5.154352
-----------------------------------+----------------------------------------------------------------
Less_than_Monthly                  |
                      intersection |
                      White Woman  |   .0269713   .1090436     0.25   0.805    -.1867503    .2406928
                     Man of Color  |   .0226764   .1552013     0.15   0.884    -.2815125    .3268654
                   Woman of Color  |   .0840282    .260939     0.32   0.747    -.4274029    .5954593
                                   |
                     civil_service |
                              Yes  |   .3681401   .0886578     4.15   0.000     .1943742    .5419061
                      weekly_hours |  -.0174145   .0051622    -3.37   0.001    -.0275322   -.0072967
                               age |   .0810023   .0394879     2.05   0.040     .0036074    .1583972
                             age_2 |  -.0006632   .0003901    -1.70   0.089    -.0014277    .0001013
                                   |
                               edu |
              High school or less  |  -.2550118   .3951896    -0.65   0.519    -1.029569    .5195456
                     Some college  |  -.2524862   .1891657    -1.33   0.182    -.6232442    .1182718
                   Graduate study  |  -.0413849   .1312833    -0.32   0.753    -.2986955    .2159258
                  Graduate degree  |  -.0305834   .1039337    -0.29   0.769    -.2342896    .1731228
                                   |
                years_employ_state |  -.0068141   .0069866    -0.98   0.329    -.0205076    .0068793
               years_employ_agency |   .0183604   .0070437     2.61   0.009     .0045551    .0321658
             years_employ_position |  -.0000655   .0085442    -0.01   0.994    -.0168119    .0166809
                                   |
                              pid5 |
                       Republican  |  -.1332501   .1321067    -1.01   0.313    -.3921745    .1256742
                  Lean Republican  |  -.0418996    .166403    -0.25   0.801    -.3680435    .2842442
                  Lean Democratic  |  -.1544347   .1548747    -1.00   0.319    -.4579835    .1491142
                       Democratic  |  -.0156411   .1205639    -0.13   0.897     -.251942    .2206598
                                   |
                       agency_size |
                           25-100  |  -.2284388   .1120045    -2.04   0.041    -.4479636    -.008914
                          101-500  |  -.3990243   .1343071    -2.97   0.003    -.6622614   -.1357873
                        501-1,000  |  -.4106973   .1886115    -2.18   0.029     -.780369   -.0410256
                      1,001-5,000  |  -.5263713   .2103803    -2.50   0.012     -.938709   -.1140336
                       Over 5,000  |  -.7192754   .3220079    -2.23   0.026    -1.350399   -.0881515
                                   |
                 log_agency_budget |  -.0785043   .0338022    -2.32   0.020    -.1447554   -.0122531
                      inst6017_nom |  -.0020287   .0048348    -0.42   0.675    -.0115048    .0074473
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .1733957   .2953256     0.59   0.557    -.4054318    .7522232
                Staff: Non-Fiscal  |  -.0566665   .2590992    -0.22   0.827    -.5644916    .4511586
Income Security & Social Services  |   .0120108   .2266521     0.05   0.958    -.4322193    .4562408
                        Education  |  -.5029735   .2510263    -2.00   0.045     -.994976    -.010971
                           Health  |  -.1434881   .2408495    -0.60   0.551    -.6155444    .3285682
                Natural Resources  |  -.0843222   .2108199    -0.40   0.689    -.4975215    .3288772
             Environment & Energy  |    -.11069   .2183167    -0.51   0.612    -.5385829    .3172029
             Economic Development  |   -.822215   .2567604    -3.20   0.001    -1.325456   -.3189738
                 Criminal Justice  |  -.3153203   .2326952    -1.36   0.175    -.7713946    .1407539
                       Regulatory  |   .2079043   .2030254     1.02   0.306    -.1900181    .6058267
                   Transportation  |    .120163   .2458099     0.49   0.625    -.3616155    .6019415
                            Other  |  -.3457758   .2229035    -1.55   0.121    -.7826587     .091107
                                   |
                             state |
                               AK  |   .3715364   .3935868     0.94   0.345    -.3998796    1.142952
                               AZ  |  -.0129197   .3967004    -0.03   0.974    -.7904382    .7645987
                               AR  |   .2960609   .4758241     0.62   0.534    -.6365371    1.228659
                               CA  |   .6249908   .3866277     1.62   0.106    -.1327855    1.382767
                               CO  |     .42197     .37914     1.11   0.266    -.3211307    1.165071
                               CT  |   .4737757   .4459715     1.06   0.288    -.4003123    1.347864
                               DE  |   .4293916   .3648889     1.18   0.239    -.2857775    1.144561
                               FL  |   .5491664   .3947635     1.39   0.164    -.2245558    1.322889
                               GA  |   .2875875   .4008785     0.72   0.473    -.4981198    1.073295
                               HI  |   .5206509    .394159     1.32   0.187    -.2518864    1.293188
                               ID  |   -.711436   .4354682    -1.63   0.102    -1.564938     .142066
                               IL  |   .6823959   .4595901     1.48   0.138    -.2183841    1.583176
                               IN  |  -.0255067   .4188369    -0.06   0.951     -.846412    .7953985
                               IA  |   .1415329   .3731353     0.38   0.704    -.5897989    .8728648
                               KS  |   .0102669   .3701262     0.03   0.978    -.7151672    .7357009
                               KY  |   .1793947   .3848407     0.47   0.641    -.5748792    .9336686
                               LA  |   .3035843    .438405     0.69   0.489    -.5556737    1.162842
                               ME  |  -.6237757   .4060349    -1.54   0.124    -1.419589    .1720381
                               MD  |   -.111841   .3829864    -0.29   0.770    -.8624805    .6387985
                               MA  |    .476464   .4274074     1.11   0.265    -.3612391    1.314167
                               MI  |   .4901141   .3826191     1.28   0.200    -.2598055    1.240034
                               MN  |    .143751   .3581039     0.40   0.688    -.5581197    .8456217
                               MS  |   .1264748   .3941461     0.32   0.748    -.6460373     .898987
                               MO  |   .6529616   .3680526     1.77   0.076    -.0684082    1.374331
                               MT  |  -.4515437    .364559    -1.24   0.215    -1.166066    .2629788
                               NE  |   .4227689   .3792934     1.11   0.265    -.3206324     1.16617
                               NV  |   -.093698   .3860246    -0.24   0.808    -.8502923    .6628964
                               NH  |   .1410811   .4027131     0.35   0.726     -.648222    .9303842
                               NJ  |   .5865558    .382465     1.53   0.125    -.1630618    1.336173
                               NM  |   .2309789   .3933707     0.59   0.557    -.5400135    1.001971
                               NY  |   .7198885   .5270917     1.37   0.172    -.3131923    1.752969
                               NC  |   .2485951   .3513564     0.71   0.479    -.4400508     .937241
                               ND  |  -.4091698   .3864658    -1.06   0.290    -1.166629    .3482892
                               OH  |   .9510652   .3881015     2.45   0.014     .1904001     1.71173
                               OK  |   -.142441   .3713454    -0.38   0.701    -.8702646    .5853826
                               OR  |   -.333197   .3956919    -0.84   0.400    -1.108739    .4423448
                               PA  |   1.287597   .3887128     3.31   0.001     .5257338     2.04946
                               RI  |   .0655188   .4535237     0.14   0.885    -.8233712    .9544089
                               SC  |  -.2076877   .3963514    -0.52   0.600    -.9845222    .5691469
                               SD  |    -.07139   .3966647    -0.18   0.857    -.8488384    .7060585
                               TN  |   .1129348   .3775371     0.30   0.765    -.6270244    .8528939
                               TX  |   .5568092   .3805468     1.46   0.143    -.1890489    1.302667
                               UT  |  -.2674936   .3604299    -0.74   0.458    -.9739232    .4389361
                               VT  |   .3127374   .3879677     0.81   0.420    -.4476654     1.07314
                               VA  |   .3928178   .4025014     0.98   0.329    -.3960704    1.181706
                               WA  |   .2024308   .3666891     0.55   0.581    -.5162666    .9211282
                               WV  |   .4118551    .390612     1.05   0.292    -.3537304    1.177441
                               WI  |   .3456722   .3728005     0.93   0.354    -.3850034    1.076348
                               WY  |  -.3385269   .3769115    -0.90   0.369     -1.07726     .400206
                                   |
                              year |
                             1984  |  -.5888546   .1485746    -3.96   0.000    -.8800556   -.2976537
                             1988  |  -.7517366   .1419305    -5.30   0.000    -1.029915    -.473558
                             1994  |   -.632151   .1490495    -4.24   0.000    -.9242827   -.3400193
                             1998  |  -.5849321   .1571894    -3.72   0.000    -.8930177   -.2768465
                             2004  |  -.4060239   .1633012    -2.49   0.013    -.7260884   -.0859594
                             2008  |  -.4322591   .1812781    -2.38   0.017    -.7875577   -.0769605
                                   |
                             _cons |  -.5434958   1.079994    -0.50   0.615    -2.660245    1.573254
-----------------------------------+----------------------------------------------------------------
Monthly                            |  (base outcome)
-----------------------------------+----------------------------------------------------------------
Weekly                             |
                      intersection |
                      White Woman  |  -.1176265   .1030639    -1.14   0.254     -.319628    .0843751
                     Man of Color  |   .0914823   .1495711     0.61   0.541    -.2016718    .3846363
                   Woman of Color  |  -.3750064   .2481364    -1.51   0.131    -.8613449     .111332
                                   |
                     civil_service |
                              Yes  |  -.5031508   .0908418    -5.54   0.000    -.6811974   -.3251042
                      weekly_hours |    .032526   .0048829     6.66   0.000     .0229557    .0420964
                               age |   .0107989   .0376123     0.29   0.774    -.0629199    .0845177
                             age_2 |  -.0000731    .000373    -0.20   0.845    -.0008042    .0006579
                                   |
                               edu |
              High school or less  |   .6338243   .3368609     1.88   0.060    -.0264109     1.29406
                     Some college  |  -.0059938   .1747545    -0.03   0.973    -.3485063    .3365187
                   Graduate study  |    .140002   .1279771     1.09   0.274    -.1108285    .3908326
                  Graduate degree  |  -.0660368   .1034105    -0.64   0.523    -.2687177    .1366441
                                   |
                years_employ_state |  -.0138005   .0062027    -2.22   0.026    -.0259575   -.0016435
               years_employ_agency |  -.0132872   .0066481    -2.00   0.046    -.0263172   -.0002572
             years_employ_position |   .0102098   .0086254     1.18   0.237    -.0066957    .0271152
                                   |
                              pid5 |
                       Republican  |   .2875126   .1267953     2.27   0.023     .0389984    .5360268
                  Lean Republican  |   .0665051   .1631966     0.41   0.684    -.2533543    .3863645
                  Lean Democratic  |  -.1556404     .15298    -1.02   0.309    -.4554758     .144195
                       Democratic  |   .2852667   .1174049     2.43   0.015     .0551573    .5153762
                                   |
                       agency_size |
                           25-100  |    -.18763    .115832    -1.62   0.105    -.4146566    .0393966
                          101-500  |   .0472405   .1317165     0.36   0.720    -.2109192    .3054001
                        501-1,000  |   .1776154   .1758797     1.01   0.313    -.1671025    .5223334
                      1,001-5,000  |   .5543342   .1856748     2.99   0.003     .1904183    .9182501
                       Over 5,000  |   .7708293   .2555947     3.02   0.003     .2698729    1.271786
                                   |
                 log_agency_budget |   .1400355   .0306427     4.57   0.000     .0799769    .2000942
                      inst6017_nom |   .0036137    .004551     0.79   0.427    -.0053062    .0125335
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .7685912   .2640216     2.91   0.004     .2511184    1.286064
                Staff: Non-Fiscal  |   .4336196   .2479697     1.75   0.080     -.052392    .9196313
Income Security & Social Services  |   -.418743   .2136899    -1.96   0.050    -.8375675    .0000814
                        Education  |  -.6082908   .2314325    -2.63   0.009     -1.06189   -.1546916
                           Health  |  -.7389156   .2261571    -3.27   0.001    -1.182175   -.2956557
                Natural Resources  |  -.2323945   .2013075    -1.15   0.248    -.6269499    .1621609
             Environment & Energy  |  -.0516428   .2092612    -0.25   0.805    -.4617873    .3585017
             Economic Development  |   .2277729   .2170865     1.05   0.294    -.1977089    .6532547
                 Criminal Justice  |  -.0744735   .2109437    -0.35   0.724    -.4879156    .3389686
                       Regulatory  |  -.4644414   .2004869    -2.32   0.021    -.8573885   -.0714942
                   Transportation  |  -.2195123   .2356173    -0.93   0.352    -.6813137    .2422891
                            Other  |  -.0236007   .2085258    -0.11   0.910    -.4323037    .3851023
                                   |
                             state |
                               AK  |   .3775514   .3618662     1.04   0.297    -.3316932    1.086796
                               AZ  |  -.2777992   .3650376    -0.76   0.447    -.9932597    .4376613
                               AR  |   1.215841   .4074771     2.98   0.003     .4172006    2.014481
                               CA  |  -1.161059   .4097886    -2.83   0.005     -1.96423   -.3578879
                               CO  |   .3643046   .3624594     1.01   0.315    -.3461028    1.074712
                               CT  |  -.0402161   .4311433    -0.09   0.926    -.8852415    .8048093
                               DE  |  -.4662626   .3608502    -1.29   0.196    -1.173516    .2409908
                               FL  |    -.51219   .3711688    -1.38   0.168    -1.239667    .2152874
                               GA  |  -.0118571   .3736604    -0.03   0.975    -.7442181    .7205038
                               HI  |  -.5433374   .3944616    -1.38   0.168    -1.316468    .2297932
                               ID  |   .5665652   .3606013     1.57   0.116    -.1402004    1.273331
                               IL  |   .0975507   .4345182     0.22   0.822    -.7540893    .9491906
                               IN  |   .2821553   .3764664     0.75   0.454    -.4557054    1.020016
                               IA  |   .2421404   .3519827     0.69   0.491    -.4477331     .932014
                               KS  |   -.111345   .3518414    -0.32   0.752    -.8009413    .5782514
                               KY  |  -.5081013   .3744767    -1.36   0.175    -1.242062    .2258595
                               LA  |   .2887177   .3919536     0.74   0.461    -.4794972    1.056933
                               ME  |  -.3033241   .3752702    -0.81   0.419     -1.03884     .432192
                               MD  |  -.3596007   .3611753    -1.00   0.319    -1.067491    .3482898
                               MA  |  -.3532822    .396683    -0.89   0.373    -1.130767    .4242022
                               MI  |   .3505255   .3712171     0.94   0.345    -.3770467    1.078098
                               MN  |  -.5413753   .3527194    -1.53   0.125    -1.232693    .1499421
                               MS  |  -.0211845   .3682821    -0.06   0.954    -.7430042    .7006353
                               MO  |  -.3650043   .3601416    -1.01   0.311    -1.070869    .3408603
                               MT  |   .4142516   .3309296     1.25   0.211    -.2343584    1.062862
                               NE  |   .3899819   .3658047     1.07   0.286    -.3269822    1.106946
                               NV  |   .0715048   .3490697     0.20   0.838    -.6126592    .7556689
                               NH  |   .5098836    .380994     1.34   0.181    -.2368508    1.256618
                               NJ  |   -.983447   .4059156    -2.42   0.015    -1.779027   -.1878671
                               NM  |  -.1534416   .3829176    -0.40   0.689    -.9039463    .5970631
                               NY  |    .259589   .5059914     0.51   0.608    -.7321358    1.251314
                               NC  |  -.7197566   .3346016    -2.15   0.031    -1.375564   -.0639495
                               ND  |   .5077531    .333553     1.52   0.128    -.1459988    1.161505
                               OH  |    .096534   .3679017     0.26   0.793      -.62454     .817608
                               OK  |  -.6373389   .3431846    -1.86   0.063    -1.309968    .0352906
                               OR  |  -.0445044   .3474177    -0.13   0.898    -.7254306    .6364219
                               PA  |  -.6941803   .3982051    -1.74   0.081    -1.474648    .0862873
                               RI  |   1.121146   .4093097     2.74   0.006     .3189139    1.923379
                               SC  |   .1135811   .3639579     0.31   0.755    -.5997632    .8269254
                               SD  |   .3059598   .3600461     0.85   0.395    -.3997176    1.011637
                               TN  |   -.879946   .3665512    -2.40   0.016    -1.598373   -.1615188
                               TX  |  -.3876095   .3739646    -1.04   0.300    -1.120567    .3453477
                               UT  |  -.1302747   .3353224    -0.39   0.698    -.7874946    .5269452
                               VT  |   .2272332    .372844     0.61   0.542    -.5035276     .957994
                               VA  |  -.2795822   .4054511    -0.69   0.490    -1.074252    .5150874
                               WA  |  -.8363528    .353453    -2.37   0.018    -1.529108   -.1435977
                               WV  |   .2587452   .3821344     0.68   0.498    -.4902244    1.007715
                               WI  |   .1216004   .3609508     0.34   0.736    -.5858502     .829051
                               WY  |   .4053564   .3321427     1.22   0.222    -.2456313    1.056344
                                   |
                              year |
                             1984  |  -.3985738   .1393845    -2.86   0.004    -.6717625   -.1253852
                             1988  |  -.5216671   .1332419    -3.92   0.000    -.7828164   -.2605178
                             1994  |   -.681269   .1414157    -4.82   0.000    -.9584387   -.4040993
                             1998  |  -.6905025   .1515222    -4.56   0.000    -.9874805   -.3935245
                             2004  |  -.6301447   .1595638    -3.95   0.000    -.9428839   -.3174055
                             2008  |   -.495696   .1701441    -2.91   0.004    -.8291722   -.1622197
                                   |
                             _cons |  -1.498662   1.017863    -1.47   0.141    -3.493636    .4963128
-----------------------------------+----------------------------------------------------------------
Daily                              |
                      intersection |
                      White Woman  |  -.2729355   .1314737    -2.08   0.038    -.5306193   -.0152518
                     Man of Color  |  -.0939457   .1923351    -0.49   0.625    -.4709156    .2830241
                   Woman of Color  |  -1.084886   .3360527    -3.23   0.001    -1.743537   -.4262346
                                   |
                     civil_service |
                              Yes  |  -1.055539   .1359697    -7.76   0.000    -1.322035   -.7890432
                      weekly_hours |   .0667231   .0061049    10.93   0.000     .0547577    .0786884
                               age |  -.0893074   .0424378    -2.10   0.035    -.1724839   -.0061309
                             age_2 |   .0008782     .00042     2.09   0.037      .000055    .0017015
                                   |
                               edu |
              High school or less  |   .2359131    .453488     0.52   0.603     -.652907    1.124733
                     Some college  |   .0082206   .2218755     0.04   0.970    -.4266475    .4430886
                   Graduate study  |   .1733141   .1615319     1.07   0.283    -.1432827    .4899109
                  Graduate degree  |   .1387833   .1316222     1.05   0.292    -.1191914     .396758
                                   |
                years_employ_state |   .0088082   .0075959     1.16   0.246    -.0060795    .0236959
               years_employ_agency |  -.0323426   .0082586    -3.92   0.000    -.0485291   -.0161561
             years_employ_position |  -.0237091   .0131682    -1.80   0.072    -.0495183    .0021002
                                   |
                              pid5 |
                       Republican  |   .5858261   .1602831     3.65   0.000     .2716769    .8999753
                  Lean Republican  |   .0711824   .2189786     0.33   0.745    -.3580077    .5003725
                  Lean Democratic  |  -.4707031   .2166537    -2.17   0.030    -.8953365   -.0460697
                       Democratic  |   .5661218   .1494077     3.79   0.000     .2732881    .8589555
                                   |
                       agency_size |
                           25-100  |  -.4700898   .1512736    -3.11   0.002    -.7665806    -.173599
                          101-500  |  -.2241542   .1653884    -1.36   0.175    -.5483096    .1000011
                        501-1,000  |   .0740033   .2212667     0.33   0.738    -.3596714     .507678
                      1,001-5,000  |   .4527819   .2263581     2.00   0.045     .0091282    .8964356
                       Over 5,000  |   1.093143   .2986453     3.66   0.000     .5078087    1.678477
                                   |
                 log_agency_budget |     .23666   .0385711     6.14   0.000     .1610621    .3122579
                      inst6017_nom |   .0018833   .0058827     0.32   0.749    -.0096465    .0134132
                                   |
                          funcat13 |
                    Staff: Fiscal  |   2.019309   .2969802     6.80   0.000     1.437239    2.601379
                Staff: Non-Fiscal  |   1.505235   .2895275     5.20   0.000     .9377712    2.072698
Income Security & Social Services  |  -.9368903   .2758518    -3.40   0.001     -1.47755   -.3962307
                        Education  |  -1.224888   .3124718    -3.92   0.000    -1.837322   -.6124551
                           Health  |  -1.366211   .3052627    -4.48   0.000    -1.964515   -.7679068
                Natural Resources  |   -.194773   .2562061    -0.76   0.447    -.6969277    .3073816
             Environment & Energy  |  -.0946499   .2722232    -0.35   0.728    -.6281975    .4388978
             Economic Development  |   .5626131   .2649435     2.12   0.034     .0433334    1.081893
                 Criminal Justice  |  -.3044534   .2761619    -1.10   0.270    -.8457208    .2368141
                       Regulatory  |  -.9924073    .281323    -3.53   0.000     -1.54379   -.4410243
                   Transportation  |  -.3772062   .2930174    -1.29   0.198    -.9515098    .1970974
                            Other  |  -.0370619   .2699427    -0.14   0.891    -.5661398     .492016
                                   |
                             state |
                               AK  |   .0194743   .3970292     0.05   0.961    -.7586887    .7976373
                               AZ  |  -.6969498   .4046604    -1.72   0.085     -1.49007    .0961699
                               AR  |   .6585641   .4484027     1.47   0.142     -.220289    1.537417
                               CA  |  -2.112896   .4663409    -4.53   0.000    -3.026908   -1.198885
                               CO  |  -.3587609   .4109467    -0.87   0.383    -1.164202    .4466798
                               CT  |  -.7304953    .528287    -1.38   0.167    -1.765919    .3049283
                               DE  |  -1.291171   .4269866    -3.02   0.002    -2.128049   -.4542924
                               FL  |   -2.26801   .4888208    -4.64   0.000    -3.226081   -1.309938
                               GA  |  -1.220568   .4697673    -2.60   0.009    -2.141295   -.2998415
                               HI  |  -1.706248   .5334652    -3.20   0.001    -2.751821   -.6606757
                               ID  |   .4466749   .3928558     1.14   0.256    -.3233083    1.216658
                               IL  |  -.0825944   .4732919    -0.17   0.861    -1.010229    .8450407
                               IN  |  -.0278532   .4005825    -0.07   0.945    -.8129804    .7572741
                               IA  |  -.6992541    .416656    -1.68   0.093    -1.515885    .1173766
                               KS  |  -1.053564   .4287292    -2.46   0.014    -1.893857   -.2132697
                               KY  |  -1.360716   .4340657    -3.13   0.002     -2.21147   -.5099632
                               LA  |  -.3379377   .4402655    -0.77   0.443    -1.200842    .5249667
                               ME  |  -.3590534   .4121313    -0.87   0.384    -1.166816     .448709
                               MD  |  -.7468056   .4081538    -1.83   0.067    -1.546772    .0531611
                               MA  |  -1.457079    .494818    -2.94   0.003    -2.426905   -.4872536
                               MI  |  -.1392178   .4251679    -0.33   0.743    -.9725316     .694096
                               MN  |  -1.778601   .4304146    -4.13   0.000    -2.622198   -.9350038
                               MS  |  -.8785612   .4444169    -1.98   0.048    -1.749602     -.00752
                               MO  |  -1.107412   .4034212    -2.75   0.006    -1.898103   -.3167207
                               MT  |   -.542643   .3863078    -1.40   0.160    -1.299792    .2145064
                               NE  |  -.3448303   .4091846    -0.84   0.399    -1.146817    .4571567
                               NV  |  -.6062522   .4075324    -1.49   0.137    -1.405001    .1924967
                               NH  |  -.0967121   .4328235    -0.22   0.823    -.9450306    .7516065
                               NJ  |  -.8219333   .4376936    -1.88   0.060    -1.679797    .0359304
                               NM  |  -.3742763   .4218321    -0.89   0.375    -1.201052    .4524995
                               NY  |   .1381132   .5485633     0.25   0.801    -.9370513    1.213278
                               NC  |  -1.450745   .3799286    -3.82   0.000    -2.195391   -.7060987
                               ND  |  -.4861639   .4076019    -1.19   0.233    -1.285049    .3127211
                               OH  |  -.9807103   .4344655    -2.26   0.024    -1.832247   -.1291734
                               OK  |  -1.388276   .3946618    -3.52   0.000    -2.161799   -.6147533
                               OR  |  -1.119592   .4235779    -2.64   0.008     -1.94979    -.289395
                               PA  |  -1.092289   .4365927    -2.50   0.012    -1.947995   -.2365828
                               RI  |   .8068291   .4569918     1.77   0.077    -.0888584    1.702517
                               SC  |  -1.093613    .481944    -2.27   0.023    -2.038206     -.14902
                               SD  |  -.1925461   .4062276    -0.47   0.636    -.9887375    .6036453
                               TN  |  -1.800417    .477996    -3.77   0.000    -2.737272   -.8635623
                               TX  |  -2.405973   .5473366    -4.40   0.000    -3.478733   -1.333213
                               UT  |  -1.177978   .3960834    -2.97   0.003    -1.954288   -.4016692
                               VT  |  -.0185495   .4009471    -0.05   0.963    -.8043914    .7672924
                               VA  |  -.5955279   .4582544    -1.30   0.194     -1.49369    .3026343
                               WA  |  -1.623074   .4202877    -3.86   0.000    -2.446822   -.7993248
                               WV  |  -.2632703   .4505351    -0.58   0.559    -1.146303    .6197623
                               WI  |  -.7268429   .4125948    -1.76   0.078    -1.535514     .081828
                               WY  |  -.2911437   .3791199    -0.77   0.443    -1.034205    .4519177
                                   |
                              year |
                             1984  |  -.3769031   .1729229    -2.18   0.029    -.7158257   -.0379804
                             1988  |  -.3602546    .161474    -2.23   0.026    -.6767379   -.0437713
                             1994  |  -.4202439   .1698925    -2.47   0.013     -.753227   -.0872607
                             1998  |  -.8003279    .189149    -4.23   0.000    -1.171053   -.4296026
                             2004  |  -.7873165   .2005841    -3.93   0.000    -1.180454   -.3941788
                             2008  |  -.6022461      .2153    -2.80   0.005    -1.024226   -.1802658
                                   |
                             _cons |  -1.200604   1.164727    -1.03   0.303    -3.483428     1.08222
----------------------------------------------------------------------------------------------------

. est sto mlogit2

. 
.  esttab mlogit2 using Table_B9.rtf  ,starlevels(+ 0.10 * 0.05 ** 0.01) cells(b(star fmt(3)) se(par fmt(3)))
>  ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Gov. Staff" ) 
(output written to Table_B9.rtf)

. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B10 ******
. mlogit reve_1c i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r, base(3)  r 

Iteration 0:   log pseudolikelihood = -10351.868  
Iteration 1:   log pseudolikelihood = -9299.7236  
Iteration 2:   log pseudolikelihood = -9078.0232  
Iteration 3:   log pseudolikelihood =  -9063.409  
Iteration 4:   log pseudolikelihood = -9061.8549  
Iteration 5:   log pseudolikelihood =  -9061.482  
Iteration 6:   log pseudolikelihood = -9061.4023  
Iteration 7:   log pseudolikelihood = -9061.3855  
Iteration 8:   log pseudolikelihood = -9061.3818  
Iteration 9:   log pseudolikelihood = -9061.3809  
Iteration 10:  log pseudolikelihood = -9061.3807  
Iteration 11:  log pseudolikelihood = -9061.3806  
Iteration 12:  log pseudolikelihood = -9061.3806  

Multinomial logistic regression                 Number of obs     =      7,543
                                                Wald chi2(372)    =   22362.67
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -9061.3806               Pseudo R2         =     0.1247

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1c |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
Never                              |
                      intersection |
                      White Woman  |   .1023515   .3667846     0.28   0.780    -.6165331    .8212361
                     Man of Color  |   .5298363   .3360172     1.58   0.115    -.1287453    1.188418
                   Woman of Color  |   .5639657   .6999624     0.81   0.420    -.8079353    1.935867
                                   |
                     civil_service |
                              Yes  |   1.302578   .2519731     5.17   0.000     .8087193    1.796436
                      weekly_hours |  -.0556317   .0118928    -4.68   0.000    -.0789411   -.0323222
                               age |  -.0872967   .0890063    -0.98   0.327    -.2617459    .0871525
                             age_2 |   .0009858   .0008272     1.19   0.233    -.0006355     .002607
                                   |
                               edu |
              High school or less  |   1.101255   .8081649     1.36   0.173    -.4827192    2.685229
                     Some college  |  -.4469582   .5252058    -0.85   0.395    -1.476343    .5824263
                   Graduate study  |   -.071533   .3864518    -0.19   0.853    -.8289647    .6858987
                  Graduate degree  |   .0097976   .2815302     0.03   0.972    -.5419915    .5615868
                                   |
                years_employ_state |   .0043349    .021189     0.20   0.838    -.0371947    .0458646
               years_employ_agency |  -.0063818   .0239083    -0.27   0.790    -.0532412    .0404776
             years_employ_position |   .0019339   .0273412     0.07   0.944    -.0516539    .0555217
                                   |
                              pid5 |
                       Republican  |  -.2401951   .3888772    -0.62   0.537     -1.00238    .5219903
                  Lean Republican  |  -.5397263    .467849    -1.15   0.249    -1.456693    .3772408
                  Lean Democratic  |  -.4263023   .4862882    -0.88   0.381     -1.37941    .5268051
                       Democratic  |  -.5464042   .3369679    -1.62   0.105    -1.206849    .1140407
                                   |
                       agency_size |
                           25-100  |  -.4490115   .2997476    -1.50   0.134    -1.036506     .138483
                          101-500  |  -.2210808   .4022883    -0.55   0.583    -1.009551    .5673899
                        501-1,000  |  -1.131687   .8241709    -1.37   0.170    -2.747033    .4836578
                      1,001-5,000  |  -.0323166   .6728416    -0.05   0.962    -1.351062    1.286429
                       Over 5,000  |  -.5676073    .987076    -0.58   0.565    -2.502241    1.367026
                                   |
                 log_agency_budget |  -.3918292   .1248561    -3.14   0.002    -.6365427   -.1471157
                      inst6017_nom |   .0155015   .0140491     1.10   0.270    -.0120342    .0430372
                                   |
                          funcat13 |
                    Staff: Fiscal  |   1.909686   1.176235     1.62   0.104    -.3956916    4.215064
                Staff: Non-Fiscal  |    1.50655   1.183303     1.27   0.203    -.8126813    3.825781
Income Security & Social Services  |   1.133771   1.222861     0.93   0.354    -1.262992    3.530534
                        Education  |   .8663485   1.295622     0.67   0.504    -1.673024    3.405722
                           Health  |   1.493802   1.168179     1.28   0.201    -.7957863    3.783391
                Natural Resources  |   .6561812   1.192007     0.55   0.582     -1.68011    2.992473
             Environment & Energy  |   .3458397   1.225184     0.28   0.778    -2.055476    2.747156
             Economic Development  |   1.229732   1.144388     1.07   0.283    -1.013227     3.47269
                 Criminal Justice  |   1.811792   1.155039     1.57   0.117    -.4520431    4.075627
                       Regulatory  |   1.151232   1.135103     1.01   0.310    -1.073528    3.375992
                   Transportation  |   1.976366   1.161436     1.70   0.089    -.3000056    4.252738
                            Other  |   1.613603   1.119198     1.44   0.149    -.5799848     3.80719
                                   |
                             state |
                               AK  |  -16.82874   .6413912   -26.24   0.000    -18.08585   -15.57164
                               AZ  |   .7855306   .9033796     0.87   0.385    -.9850609    2.556122
                               AR  |  -.3210395   1.245909    -0.26   0.797    -2.762976    2.120897
                               CA  |   .7985362   1.020665     0.78   0.434     -1.20193    2.799003
                               CO  |  -17.13557   .6274608   -27.31   0.000    -18.36537   -15.90577
                               CT  |   .3075978   .8819384     0.35   0.727     -1.42097    2.036165
                               DE  |  -16.84698   .6687362   -25.19   0.000    -18.15768   -15.53628
                               FL  |   .1547643    1.26634     0.12   0.903    -2.327216    2.636745
                               GA  |  -.4486227   1.164382    -0.39   0.700    -2.730769    1.833524
                               HI  |   .6906851    .775198     0.89   0.373    -.8286752    2.210045
                               ID  |  -.6150492   1.185167    -0.52   0.604    -2.937935    1.707836
                               IL  |  -.1425382   1.278973    -0.11   0.911    -2.649278    2.364202
                               IN  |    .319864   .9201613     0.35   0.728    -1.483619    2.123347
                               IA  |  -16.78043   .6179809   -27.15   0.000    -17.99165   -15.56921
                               KS  |  -1.005065   1.188312    -0.85   0.398    -3.334114    1.323984
                               KY  |    .530666   .9009536     0.59   0.556    -1.235171    2.296503
                               LA  |  -.4850458    1.11975    -0.43   0.665    -2.679716    1.709625
                               ME  |  -.8918776   1.252474    -0.71   0.476    -3.346681    1.562926
                               MD  |  -16.63777   .6655658   -25.00   0.000    -17.94225   -15.33328
                               MA  |  -.0496523    1.22928    -0.04   0.968    -2.458997    2.359693
                               MI  |  -1.012357   1.229222    -0.82   0.410    -3.421588    1.396874
                               MN  |   .1355171   .8190817     0.17   0.869    -1.469854    1.740888
                               MS  |   .2476053   .8047239     0.31   0.758    -1.329625    1.824835
                               MO  |   .7447108   .8295341     0.90   0.369    -.8811461    2.370568
                               MT  |    -.37048   .8395908    -0.44   0.659    -2.016048    1.275088
                               NE  |  -.7591477   1.269776    -0.60   0.550    -3.247864    1.729568
                               NV  |  -.3544017   .9449925    -0.38   0.708    -2.206553     1.49775
                               NH  |  -16.78527   .6545801   -25.64   0.000    -18.06823   -15.50232
                               NJ  |   1.274665   .8291024     1.54   0.124    -.3503458    2.899676
                               NM  |    .295328   .8358299     0.35   0.724    -1.342868    1.933524
                               NY  |   1.481001   .8819718     1.68   0.093    -.2476318    3.209634
                               NC  |  -16.64434   .6531247   -25.48   0.000    -17.92444   -15.36424
                               ND  |  -17.40199    .622479   -27.96   0.000    -18.62203   -16.18196
                               OH  |     .88853   .9030208     0.98   0.325    -.8813583    2.658418
                               OK  |   .1942424   .8300852     0.23   0.815    -1.432695     1.82118
                               OR  |  -1.067231   1.258821    -0.85   0.397    -3.534475    1.400012
                               PA  |   .7031443   .8676387     0.81   0.418    -.9973963    2.403685
                               RI  |   -.194349   .8331127    -0.23   0.816     -1.82722    1.438522
                               SC  |   .7131492   .8899515     0.80   0.423    -1.031124    2.457422
                               SD  |  -17.01963   .6505886   -26.16   0.000    -18.29476    -15.7445
                               TN  |  -16.45451   .6344546   -25.93   0.000    -17.69802     -15.211
                               TX  |   1.379927   .7725064     1.79   0.074    -.1341577    2.894012
                               UT  |   .0819992   .9074691     0.09   0.928    -1.696608    1.860606
                               VT  |  -16.87679    .652167   -25.88   0.000    -18.15501   -15.59856
                               VA  |   .6651276   .9202771     0.72   0.470    -1.138582    2.468838
                               WA  |   -.703441   1.207953    -0.58   0.560    -3.070985    1.664103
                               WV  |  -.1366168    .899094    -0.15   0.879    -1.898809    1.625575
                               WI  |   -.237986   .9344865    -0.25   0.799    -2.069546    1.593574
                               WY  |   .5742965   .8527547     0.67   0.501    -1.097072    2.245665
                                   |
                              year |
                             1978  |   1.420906   .6985485     2.03   0.042     .0517764    2.790036
                             1984  |   1.826943   .7085779     2.58   0.010     .4381557     3.21573
                             1988  |   1.167486   .7373451     1.58   0.113    -.2776835    2.612656
                             1994  |   .8967173   .8009197     1.12   0.263    -.6730565    2.466491
                             1998  |   1.891739   .6888063     2.75   0.006     .5417033    3.241774
                             2004  |   2.239535   .6821644     3.28   0.001     .9025172    3.576553
                             2008  |   3.040197   .7061401     4.31   0.000     1.656188    4.424206
                                   |
                             _cons |  -1.233859   3.089438    -0.40   0.690    -7.289047    4.821328
-----------------------------------+----------------------------------------------------------------
Less_than_Monthly                  |
                      intersection |
                      White Woman  |    .192433   .0977116     1.97   0.049     .0009217    .3839442
                     Man of Color  |   .4536013    .127295     3.56   0.000     .2041077     .703095
                   Woman of Color  |   .5176247   .2327668     2.22   0.026     .0614102    .9738393
                                   |
                     civil_service |
                              Yes  |   .2173737   .0775857     2.80   0.005     .0653086    .3694389
                      weekly_hours |  -.0182583   .0042439    -4.30   0.000    -.0265762   -.0099403
                               age |    .035844   .0315645     1.14   0.256    -.0260212    .0977092
                             age_2 |  -.0002378   .0003149    -0.76   0.450    -.0008549    .0003793
                                   |
                               edu |
              High school or less  |   .3325092    .282109     1.18   0.239    -.2204142    .8854327
                     Some college  |   .2410346   .1453077     1.66   0.097    -.0437633    .5258326
                   Graduate study  |   .0407997   .1094942     0.37   0.709     -.173805    .2554043
                  Graduate degree  |    .112805   .0886201     1.27   0.203    -.0608873    .2864972
                                   |
                years_employ_state |   .0102333   .0058499     1.75   0.080    -.0012323     .021699
               years_employ_agency |   .0003139   .0061375     0.05   0.959    -.0117155    .0123432
             years_employ_position |    -.01452   .0077419    -1.88   0.061    -.0296937    .0006538
                                   |
                              pid5 |
                       Republican  |  -.0557857   .1143734    -0.49   0.626    -.2799535     .168382
                  Lean Republican  |   .0333462   .1408133     0.24   0.813    -.2426427    .3093352
                  Lean Democratic  |  -.1545379    .137904    -1.12   0.262    -.4248247     .115749
                       Democratic  |  -.0410798   .1064211    -0.39   0.699    -.2496613    .1675017
                                   |
                       agency_size |
                           25-100  |  -.2310172   .0924764    -2.50   0.012    -.4122677   -.0497667
                          101-500  |  -.2755294   .1124976    -2.45   0.014    -.4960207   -.0550381
                        501-1,000  |  -.3540081   .1606643    -2.20   0.028    -.6689044   -.0391118
                      1,001-5,000  |  -.0694188   .1699253    -0.41   0.683    -.4024663    .2636288
                       Over 5,000  |  -.5685089   .2669593    -2.13   0.033    -1.091739   -.0452784
                                   |
                 log_agency_budget |  -.1081004   .0285332    -3.79   0.000    -.1640244   -.0521763
                      inst6017_nom |   .0030083   .0039639     0.76   0.448    -.0047608    .0107773
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .2402335   .2504344     0.96   0.337    -.2506089    .7310759
                Staff: Non-Fiscal  |   .3625476   .2398591     1.51   0.131    -.1075676    .8326629
Income Security & Social Services  |   .1499969   .2349677     0.64   0.523    -.3105314    .6105252
                        Education  |   .1916814    .253874     0.76   0.450    -.3059024    .6892653
                           Health  |   -.047191   .2489434    -0.19   0.850    -.5351111    .4407291
                Natural Resources  |  -.0557786   .2258595    -0.25   0.805    -.4984551    .3868979
             Environment & Energy  |   .2922736   .2281462     1.28   0.200    -.1548848     .739432
             Economic Development  |    .122444    .233948     0.52   0.601    -.3360857    .5809737
                 Criminal Justice  |   .2375871   .2304661     1.03   0.303    -.2141181    .6892922
                       Regulatory  |   .4960447   .2192517     2.26   0.024     .0663192    .9257702
                   Transportation  |   .3326481   .2474823     1.34   0.179    -.1524083    .8177044
                            Other  |   .2961961   .2251935     1.32   0.188     -.145175    .7375672
                                   |
                             state |
                               AK  |  -.3462208   .3020505    -1.15   0.252    -.9382289    .2457872
                               AZ  |   .0903868   .3325236     0.27   0.786    -.5613475    .7421211
                               AR  |  -.0206095   .3457556    -0.06   0.952    -.6982781    .6570591
                               CA  |  -.2576217   .3629287    -0.71   0.478    -.9689489    .4537054
                               CO  |  -.5557902   .3061436    -1.82   0.069    -1.155821    .0442402
                               CT  |  -.9343993   .3956167    -2.36   0.018    -1.709794   -.1590049
                               DE  |  -.2221608    .319008    -0.70   0.486    -.8474049    .4030833
                               FL  |   .0700506   .3266577     0.21   0.830    -.5701867    .7102879
                               GA  |  -.6696292   .3548637    -1.89   0.059    -1.365149    .0258908
                               HI  |   .1211999   .3303615     0.37   0.714    -.5262967    .7686966
                               ID  |    .133752    .313574     0.43   0.670    -.4808418    .7483458
                               IL  |  -.1794818   .3790217    -0.47   0.636    -.9223506    .5633871
                               IN  |  -.3572557   .3197911    -1.12   0.264    -.9840348    .2695233
                               IA  |  -.3076764   .3010711    -1.02   0.307    -.8977649    .2824122
                               KS  |  -.5071102   .3244722    -1.56   0.118    -1.143064    .1288436
                               KY  |   .0689504   .3245604     0.21   0.832    -.5671764    .7050772
                               LA  |   .0337378   .3637813     0.09   0.926    -.6792605     .746736
                               ME  |  -.5542549   .3647094    -1.52   0.129    -1.269072    .1605625
                               MD  |  -.5986974   .3323955    -1.80   0.072    -1.250181    .0527858
                               MA  |   -.541771    .382427    -1.42   0.157    -1.291314    .2077721
                               MI  |  -.4663476   .3526484    -1.32   0.186    -1.157526    .2248306
                               MN  |  -.8720754   .3337977    -2.61   0.009    -1.526307   -.2178439
                               MS  |  -.5390633   .3403347    -1.58   0.113    -1.206107    .1279804
                               MO  |  -.0447453   .3380115    -0.13   0.895    -.7072357     .617745
                               MT  |  -.0004477   .2911207    -0.00   0.999    -.5710339    .5701384
                               NE  |   .0512744    .307041     0.17   0.867    -.5505149    .6530636
                               NV  |  -.0395919   .2913348    -0.14   0.892    -.6105976    .5314139
                               NH  |  -.9584945   .3682638    -2.60   0.009    -1.680278   -.2367107
                               NJ  |   .1693336   .3215557     0.53   0.598     -.460904    .7995712
                               NM  |   .0206687   .3117543     0.07   0.947    -.5903584    .6316959
                               NY  |  -.0199122   .3697784    -0.05   0.957    -.7446646    .7048402
                               NC  |  -.3550388   .2928425    -1.21   0.225    -.9289996    .2189219
                               ND  |  -.2264823   .2897493    -0.78   0.434    -.7943805    .3414159
                               OH  |  -.0029807   .3115358    -0.01   0.992    -.6135796    .6076183
                               OK  |  -.6563379   .3389558    -1.94   0.053    -1.320679    .0080032
                               OR  |  -.3360902   .3070171    -1.09   0.274    -.9378326    .2656522
                               PA  |  -.1561612   .3430953    -0.46   0.649    -.8286156    .5162931
                               RI  |  -.3702295   .3272246    -1.13   0.258    -1.011578     .271119
                               SC  |  -.7212634   .3795847    -1.90   0.057    -1.465236    .0227089
                               SD  |   .4353311   .2967223     1.47   0.142     -.146234    1.016896
                               TN  |  -.3028604   .3325595    -0.91   0.362    -.9546651    .3489442
                               TX  |   -.248752   .3536609    -0.70   0.482    -.9419147    .4444106
                               UT  |  -.0631828   .2863601    -0.22   0.825    -.6244382    .4980726
                               VT  |  -.5595125   .3425895    -1.63   0.102    -1.230976    .1119505
                               VA  |  -.2274623   .3262896    -0.70   0.486    -.8669782    .4120537
                               WA  |  -.1171899   .3094067    -0.38   0.705     -.723616    .4892361
                               WV  |   .0716697   .3083681     0.23   0.816    -.5327206      .67606
                               WI  |  -.7832454   .3273501    -2.39   0.017     -1.42484   -.1416509
                               WY  |   .5051549   .2922124     1.73   0.084    -.0675709    1.077881
                                   |
                              year |
                             1978  |   .0823197   .1294459     0.64   0.525    -.1713897    .3360291
                             1984  |  -.2025204   .1293849    -1.57   0.118    -.4561102    .0510694
                             1988  |  -.1979383   .1218102    -1.62   0.104    -.4366819    .0408054
                             1994  |   -.284856   .1292345    -2.20   0.028    -.5381509    -.031561
                             1998  |  -.2987716   .1326776    -2.25   0.024    -.5588149   -.0387283
                             2004  |  -.0916702   .1363944    -0.67   0.502    -.3589982    .1756579
                             2008  |  -.1574201   .1519833    -1.04   0.300    -.4553019    .1404616
                                   |
                             _cons |  -.1287268   .8798041    -0.15   0.884    -1.853111    1.595658
-----------------------------------+----------------------------------------------------------------
Monthly                            |  (base outcome)
-----------------------------------+----------------------------------------------------------------
Weekly                             |
                      intersection |
                      White Woman  |  -.0800817    .094301    -0.85   0.396    -.2649082    .1047448
                     Man of Color  |  -.2325181   .1383378    -1.68   0.093    -.5036553     .038619
                   Woman of Color  |  -.2799827   .2631272    -1.06   0.287    -.7957025     .235737
                                   |
                     civil_service |
                              Yes  |  -.3360183   .0800533    -4.20   0.000    -.4929198   -.1791167
                      weekly_hours |   .0273546   .0040764     6.71   0.000      .019365    .0353441
                               age |  -.0214226   .0302588    -0.71   0.479    -.0807287    .0378835
                             age_2 |   .0001125   .0003014     0.37   0.709    -.0004782    .0007032
                                   |
                               edu |
              High school or less  |   .5693535   .2732022     2.08   0.037     .0338872     1.10482
                     Some college  |   .0576172   .1489495     0.39   0.699    -.2343185    .3495529
                   Graduate study  |   .1731688   .1081988     1.60   0.109    -.0388969    .3852345
                  Graduate degree  |   .1691091   .0869802     1.94   0.052     -.001369    .3395871
                                   |
                years_employ_state |   .0137949   .0055646     2.48   0.013     .0028884    .0247014
               years_employ_agency |  -.0169424   .0059129    -2.87   0.004    -.0285315   -.0053534
             years_employ_position |   .0011376    .007693     0.15   0.882    -.0139403    .0162156
                                   |
                              pid5 |
                       Republican  |   .2648727   .1110723     2.38   0.017      .047175    .4825705
                  Lean Republican  |  -.0466882   .1417966    -0.33   0.742    -.3246044    .2312279
                  Lean Democratic  |   -.152388   .1347293    -1.13   0.258    -.4164526    .1116766
                       Democratic  |   .1220252    .103986     1.17   0.241    -.0817836     .325834
                                   |
                       agency_size |
                           25-100  |   .1184451   .1015519     1.17   0.243    -.0805929    .3174831
                          101-500  |   .3289427   .1136779     2.89   0.004     .1061381    .5517473
                        501-1,000  |   .2849422    .149563     1.91   0.057    -.0081959    .5780804
                      1,001-5,000  |   .5436483   .1558122     3.49   0.000      .238262    .8490347
                       Over 5,000  |   .4389584   .2180272     2.01   0.044     .0116329    .8662839
                                   |
                 log_agency_budget |    .113738   .0264506     4.30   0.000     .0618958    .1655802
                      inst6017_nom |   .0100423   .0037785     2.66   0.008     .0026365    .0174481
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.9405089     .20866    -4.51   0.000    -1.349475   -.5315428
                Staff: Non-Fiscal  |  -1.113648   .2035728    -5.47   0.000    -1.512643   -.7146525
Income Security & Social Services  |  -1.456766   .1939186    -7.51   0.000     -1.83684   -1.076693
                        Education  |   -1.03215   .2107644    -4.90   0.000     -1.44524   -.6190589
                           Health  |  -1.307198   .1999551    -6.54   0.000    -1.699103   -.9152936
                Natural Resources  |  -1.009521   .1801795    -5.60   0.000    -1.362667    -.656376
             Environment & Energy  |  -.8432022   .1878631    -4.49   0.000    -1.211407   -.4749972
             Economic Development  |  -1.040357   .1912225    -5.44   0.000    -1.415147    -.665568
                 Criminal Justice  |  -1.239543   .1912786    -6.48   0.000    -1.614443   -.8646442
                       Regulatory  |  -.9244247   .1801937    -5.13   0.000    -1.277598   -.5712515
                   Transportation  |  -.9976233   .2113315    -4.72   0.000    -1.411825   -.5834212
                            Other  |  -1.279542   .1915901    -6.68   0.000    -1.655051   -.9040319
                                   |
                             state |
                               AK  |  -.5443526   .3034109    -1.79   0.073    -1.139027    .0503218
                               AZ  |   .0260728   .3219463     0.08   0.935    -.6049304     .657076
                               AR  |   .0659155   .3265979     0.20   0.840    -.5742045    .7060356
                               CA  |    -.36096   .3274824    -1.10   0.270    -1.002814    .2808938
                               CO  |  -.1804299   .2949012    -0.61   0.541    -.7584256    .3975658
                               CT  |  -.4278183   .3388404    -1.26   0.207    -1.091933    .2362967
                               DE  |  -.3699698   .3103059    -1.19   0.233    -.9781582    .2382185
                               FL  |  -.6211213   .3133795    -1.98   0.047    -1.235334   -.0069087
                               GA  |  -.1213602   .3061152    -0.40   0.692    -.7213349    .4786146
                               HI  |  -.5786476   .3558584    -1.63   0.104    -1.276117    .1188221
                               ID  |   .0674986   .3112966     0.22   0.828    -.5426315    .6776287
                               IL  |  -.0844451   .3342852    -0.25   0.801    -.7396321    .5707419
                               IN  |  -.7112374   .3152685    -2.26   0.024    -1.329152   -.0933225
                               IA  |  -.6525648   .2991825    -2.18   0.029    -1.238952   -.0661779
                               KS  |   .2015155   .3041322     0.66   0.508    -.3945726    .7976037
                               KY  |  -.4890194   .3242195    -1.51   0.131    -1.124478    .1464391
                               LA  |   .2301759   .3478083     0.66   0.508    -.4515159    .9118677
                               ME  |   .4669057   .3175293     1.47   0.141    -.1554404    1.089252
                               MD  |  -.2299558   .2995699    -0.77   0.443    -.8171021    .3571905
                               MA  |  -.2638498   .3338969    -0.79   0.429    -.9182757    .3905762
                               MI  |   .3934687    .310441     1.27   0.205    -.2149846    1.001922
                               MN  |   -.199155   .2921888    -0.68   0.495    -.7718346    .3735246
                               MS  |  -.0522108   .3176502    -0.16   0.869    -.6747938    .5703721
                               MO  |    .407303   .3059015     1.33   0.183     -.192253    1.006859
                               MT  |  -.3587377   .3018395    -1.19   0.235    -.9503323    .2328569
                               NE  |  -.2319693   .3022137    -0.77   0.443    -.8242972    .3603587
                               NV  |  -1.113043   .3214584    -3.46   0.001     -1.74309   -.4829958
                               NH  |   .4850265   .3070833     1.58   0.114    -.1168457    1.086899
                               NJ  |  -.5768036   .3265893    -1.77   0.077    -1.216907    .0632996
                               NM  |  -.6032408   .3312316    -1.82   0.069    -1.252443    .0459612
                               NY  |  -.6394186   .3539546    -1.81   0.071    -1.333157    .0543196
                               NC  |  -.5271114   .2798317    -1.88   0.060    -1.075571    .0213488
                               ND  |  -.7832097    .303873    -2.58   0.010     -1.37879   -.1876295
                               OH  |  -.4989035   .3037279    -1.64   0.100    -1.094199    .0963923
                               OK  |  -.1751177   .3081495    -0.57   0.570    -.7790797    .4288443
                               OR  |  -.7455785   .3024153    -2.47   0.014    -1.338301   -.1528554
                               PA  |  -.2217302   .3152136    -0.70   0.482    -.8395374    .3960771
                               RI  |  -.6631482   .3346645    -1.98   0.048    -1.319079   -.0072179
                               SC  |   .3209176   .3238754     0.99   0.322    -.3138665    .9557016
                               SD  |  -.9364017   .3246078    -2.88   0.004    -1.572621   -.3001822
                               TN  |  -.5034239   .3189779    -1.58   0.115    -1.128609    .1217614
                               TX  |  -.1279471   .3223024    -0.40   0.691    -.7596482    .5037539
                               UT  |  -.8781425   .3072359    -2.86   0.004    -1.480314   -.2759712
                               VT  |   .0853471   .3101575     0.28   0.783    -.5225504    .6932446
                               VA  |  -.5259035   .3191328    -1.65   0.099    -1.151392    .0995854
                               WA  |  -.6851627   .3059934    -2.24   0.025    -1.284899   -.0854267
                               WV  |  -.4611654   .3147112    -1.47   0.143    -1.077988    .1556573
                               WI  |  -.2222828   .2944087    -0.76   0.450    -.7993133    .3547477
                               WY  |  -.3144046   .3105644    -1.01   0.311    -.9230997    .2942905
                                   |
                              year |
                             1978  |  -.2707126   .1243684    -2.18   0.030    -.5144702    -.026955
                             1984  |  -.4521321   .1233977    -3.66   0.000    -.6939872    -.210277
                             1988  |  -.3741088   .1142748    -3.27   0.001    -.5980833   -.1501342
                             1994  |  -.4233292   .1212045    -3.49   0.000    -.6608856   -.1857728
                             1998  |  -.5901975   .1258193    -4.69   0.000    -.8367987   -.3435962
                             2004  |  -.6917118   .1355024    -5.10   0.000    -.9572916    -.426132
                             2008  |   -.723974   .1460754    -4.96   0.000    -1.010276   -.4376716
                                   |
                             _cons |  -.1210709   .8330088    -0.15   0.884    -1.753738    1.511596
-----------------------------------+----------------------------------------------------------------
Daily                              |
                      intersection |
                      White Woman  |   -.067038   .1489363    -0.45   0.653    -.3589479    .2248718
                     Man of Color  |  -.5071535   .2258443    -2.25   0.025    -.9498002   -.0645069
                   Woman of Color  |  -.5496631   .4272747    -1.29   0.198    -1.387106    .2877798
                                   |
                     civil_service |
                              Yes  |  -.5441517   .1269908    -4.28   0.000    -.7930491   -.2952543
                      weekly_hours |   .0575891   .0056343    10.22   0.000     .0465461    .0686321
                               age |    .011922   .0465701     0.26   0.798    -.0793537    .1031976
                             age_2 |  -.0002227   .0004784    -0.47   0.641    -.0011604    .0007149
                                   |
                               edu |
              High school or less  |   .3461838   .3915842     0.88   0.377    -.4213071    1.113675
                     Some college  |  -.1179222   .2134783    -0.55   0.581     -.536332    .3004876
                   Graduate study  |   .2138864    .154706     1.38   0.167    -.0893318    .5171046
                  Graduate degree  |   .1695648   .1271303     1.33   0.182    -.0796059    .4187356
                                   |
                years_employ_state |   .0187142   .0077293     2.42   0.015     .0035652    .0338633
               years_employ_agency |   -.016083    .008344    -1.93   0.054    -.0324369    .0002709
             years_employ_position |   .0024618   .0109815     0.22   0.823    -.0190616    .0239851
                                   |
                              pid5 |
                       Republican  |   .2670781   .1616415     1.65   0.098    -.0497334    .5838896
                  Lean Republican  |  -.0530916   .2150386    -0.25   0.805    -.4745596    .3683764
                  Lean Democratic  |  -.1876142    .199868    -0.94   0.348    -.5793483    .2041199
                       Democratic  |   .2351323   .1502122     1.57   0.118    -.0592783    .5295428
                                   |
                       agency_size |
                           25-100  |    .007421    .164285     0.05   0.964    -.3145716    .3294137
                          101-500  |   .3897487   .1785117     2.18   0.029     .0398723    .7396252
                        501-1,000  |   .5951502   .2295143     2.59   0.010     .1453104     1.04499
                      1,001-5,000  |   .9734838   .2346914     4.15   0.000     .5134971    1.433471
                       Over 5,000  |   1.289765   .3076602     4.19   0.000     .6867624    1.892768
                                   |
                 log_agency_budget |   .1153989   .0423423     2.73   0.006     .0324096    .1983882
                      inst6017_nom |   .0106335   .0055986     1.90   0.058    -.0003394    .0216065
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.7918185   .2424022    -3.27   0.001    -1.266918   -.3167188
                Staff: Non-Fiscal  |  -1.837837   .2695854    -6.82   0.000    -2.366214   -1.309459
Income Security & Social Services  |  -2.485754    .257301    -9.66   0.000    -2.990054   -1.981453
                        Education  |  -2.185672   .3018842    -7.24   0.000    -2.777354    -1.59399
                           Health  |  -2.881302   .2907433    -9.91   0.000    -3.451148   -2.311456
                Natural Resources  |  -1.700711   .2265635    -7.51   0.000    -2.144768   -1.256655
             Environment & Energy  |  -2.000116   .2578431    -7.76   0.000    -2.505479   -1.494753
             Economic Development  |  -1.836513   .2501363    -7.34   0.000    -2.326771   -1.346255
                 Criminal Justice  |  -2.444234   .2590014    -9.44   0.000    -2.951868   -1.936601
                       Regulatory  |  -1.850335   .2376988    -7.78   0.000    -2.316216   -1.384454
                   Transportation  |  -1.030628   .2473608    -4.17   0.000    -1.515446   -.5458098
                            Other  |  -2.224197   .2681762    -8.29   0.000    -2.749812   -1.698581
                                   |
                             state |
                               AK  |   .5027026    .482267     1.04   0.297    -.4425233    1.447929
                               AZ  |   .7569256   .5117974     1.48   0.139    -.2461788     1.76003
                               AR  |   1.295926   .4894619     2.65   0.008     .3365982    2.255254
                               CA  |  -.2236881   .5366555    -0.42   0.677    -1.275514    .8281374
                               CO  |   .4240619   .4899301     0.87   0.387    -.5361835    1.384307
                               CT  |  -.0790308     .56341    -0.14   0.888    -1.183294    1.025233
                               DE  |   .5916034   .4942943     1.20   0.231    -.3771956    1.560402
                               FL  |  -.8182744   .5459038    -1.50   0.134    -1.888226    .2516775
                               GA  |   .3302814   .4900547     0.67   0.500    -.6302081    1.290771
                               HI  |  -.0330264   .5928227    -0.06   0.956    -1.194938    1.128885
                               ID  |   .2646588   .5253466     0.50   0.614    -.7650016    1.294319
                               IL  |   .2920561   .5381549     0.54   0.587    -.7627082     1.34682
                               IN  |  -.5246623   .5239195    -1.00   0.317    -1.551526     .502201
                               IA  |   .1352399   .4893928     0.28   0.782    -.8239524    1.094432
                               KS  |   .6194871   .5077284     1.22   0.222    -.3756422    1.614617
                               KY  |  -1.218392   .6370634    -1.91   0.056    -2.467013     .030229
                               LA  |   1.373634     .50821     2.70   0.007     .3775608    2.369707
                               ME  |   .9392171   .5098438     1.84   0.065    -.0600583    1.938493
                               MD  |  -.2098746   .5229681    -0.40   0.688    -1.234873     .815124
                               MA  |   .5892389   .5037265     1.17   0.242    -.3980468    1.576525
                               MI  |   1.160209   .4934828     2.35   0.019     .1930005    2.127418
                               MN  |   .0523342   .5015198     0.10   0.917    -.9306266    1.035295
                               MS  |   .3856267   .5273325     0.73   0.465    -.6479261    1.419179
                               MO  |   .5891904   .5000038     1.18   0.239    -.3907991     1.56918
                               MT  |  -.6189168    .569815    -1.09   0.277    -1.735734    .4979001
                               NE  |   .2204107   .5040421     0.44   0.662    -.7674937    1.208315
                               NV  |  -2.207449   .8381171    -2.63   0.008    -3.850129   -.5647699
                               NH  |    1.23782   .4974108     2.49   0.013     .2629127    2.212727
                               NJ  |  -.0519849   .5268108    -0.10   0.921    -1.084515    .9805452
                               NM  |  -.3892564   .5757036    -0.68   0.499    -1.517615    .7391019
                               NY  |  -.5771294   .5618856    -1.03   0.304    -1.678405    .5241462
                               NC  |  -.5324447   .4916862    -1.08   0.279    -1.496132    .4312426
                               ND  |  -2.246231   .8511565    -2.64   0.008    -3.914467   -.5779947
                               OH  |  -.5151934   .5285474    -0.97   0.330    -1.551127    .5207405
                               OK  |   1.284413   .4701412     2.73   0.006     .3629535    2.205873
                               OR  |  -.6810203   .5221915    -1.30   0.192    -1.704497    .3424563
                               PA  |   .3086373   .4901194     0.63   0.529    -.6519792    1.269254
                               RI  |   .1643992   .5494635     0.30   0.765    -.9125294    1.241328
                               SC  |   1.601199   .4867068     3.29   0.001      .647271    2.555127
                               SD  |   -1.06288   .6127182    -1.73   0.083    -2.263785    .1380261
                               TN  |   .2274341   .5089309     0.45   0.655    -.7700521     1.22492
                               TX  |   .0731096   .5400087     0.14   0.892    -.9852881    1.131507
                               UT  |  -1.184048    .609419    -1.94   0.052    -2.378488     .010391
                               VT  |    .969353   .4879598     1.99   0.047     .0129693    1.925737
                               VA  |  -.5859897   .5744197    -1.02   0.308    -1.711832    .5398521
                               WA  |  -.7766725   .5267749    -1.47   0.140    -1.809132    .2557873
                               WV  |  -.5974807   .5589078    -1.07   0.285     -1.69292    .4979584
                               WI  |  -.3337446   .5039266    -0.66   0.508    -1.321423    .6539334
                               WY  |  -1.896918   .8374162    -2.27   0.024    -3.538223   -.2556121
                                   |
                              year |
                             1978  |  -.8376392   .1598436    -5.24   0.000    -1.150927   -.5243514
                             1984  |  -1.108735    .163919    -6.76   0.000     -1.43001   -.7874594
                             1988  |  -1.092508   .1515319    -7.21   0.000    -1.389505    -.795511
                             1994  |  -1.204815   .1670699    -7.21   0.000    -1.532266   -.8773644
                             1998  |  -1.842342   .1907807    -9.66   0.000    -2.216266   -1.468419
                             2004  |  -2.288408   .2298031    -9.96   0.000    -2.738813   -1.838002
                             2008  |  -1.917361   .2443744    -7.85   0.000    -2.396325   -1.438396
                                   |
                             _cons |   -2.97092   1.246589    -2.38   0.017     -5.41419   -.5276508
----------------------------------------------------------------------------------------------------

. est sto mlogit3

. 
.  esttab mlogit3 using Table_B10.rtf  ,starlevels(+ 0.10 * 0.05 ** 0.01) cells(b(star fmt(3)) se(par fmt(3))
> ) ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Legis." ) 
(output written to Table_B10.rtf)

. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B11 ******
. mlogit reve_1d i.intersection i.civil_service weekly_hours age age_2 b3.edu years_employ_state years_employ
> _agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom i.funcat13 i.state i.yea
> r, base(3)  r  

Iteration 0:   log pseudolikelihood = -8728.3519  
Iteration 1:   log pseudolikelihood = -8124.4005  
Iteration 2:   log pseudolikelihood = -8006.8635  
Iteration 3:   log pseudolikelihood =  -8002.341  
Iteration 4:   log pseudolikelihood = -8001.5892  
Iteration 5:   log pseudolikelihood =  -8001.414  
Iteration 6:   log pseudolikelihood = -8001.3725  
Iteration 7:   log pseudolikelihood =  -8001.364  
Iteration 8:   log pseudolikelihood = -8001.3627  
Iteration 9:   log pseudolikelihood = -8001.3623  
Iteration 10:  log pseudolikelihood = -8001.3623  
Iteration 11:  log pseudolikelihood = -8001.3623  

Multinomial logistic regression                 Number of obs     =      6,340
                                                Wald chi2(368)    =   30131.78
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -8001.3623               Pseudo R2         =     0.0833

----------------------------------------------------------------------------------------------------
                                   |               Robust
                           reve_1d |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
Never                              |
                      intersection |
                      White Woman  |   .0540897     .25926     0.21   0.835    -.4540506      .56223
                     Man of Color  |   .5311472   .2979999     1.78   0.075    -.0529219    1.115216
                   Woman of Color  |    1.55397   .4969584     3.13   0.002     .5799492    2.527991
                                   |
                     civil_service |
                              Yes  |   .3191978   .2016497     1.58   0.113    -.0760284    .7144241
                      weekly_hours |   -.023182    .010228    -2.27   0.023    -.0432285   -.0031356
                               age |  -.0297909   .0742274    -0.40   0.688    -.1752739    .1156922
                             age_2 |   .0004329    .000713     0.61   0.544    -.0009644    .0018303
                                   |
                               edu |
              High school or less  |   .0149574   .7864379     0.02   0.985    -1.526433    1.556347
                     Some college  |   .2165916   .4236454     0.51   0.609     -.613738    1.046921
                   Graduate study  |   .0614352   .2932174     0.21   0.834    -.5132604    .6361309
                  Graduate degree  |    .032926   .2283624     0.14   0.885    -.4146561     .480508
                                   |
                years_employ_state |  -.0134073   .0159317    -0.84   0.400    -.0446328    .0178183
               years_employ_agency |   .0023601    .015874     0.15   0.882    -.0287523    .0334725
             years_employ_position |  -.0119336   .0221922    -0.54   0.591    -.0554296    .0315623
                                   |
                              pid5 |
                       Republican  |   .1310773   .3034639     0.43   0.666     -.463701    .7258556
                  Lean Republican  |    .198782   .3775446     0.53   0.599    -.5411918    .9387557
                  Lean Democratic  |   .5348731   .3565884     1.50   0.134    -.1640275    1.233774
                       Democratic  |   .0175646   .2752992     0.06   0.949    -.5220119    .5571412
                                   |
                       agency_size |
                           25-100  |  -.2427945   .2411191    -1.01   0.314    -.7153792    .2297902
                          101-500  |  -.4184722   .2949404    -1.42   0.156    -.9965447    .1596003
                        501-1,000  |  -.3104106   .4045278    -0.77   0.443    -1.103271    .4824494
                      1,001-5,000  |   .2170397   .4522634     0.48   0.631    -.6693802     1.10346
                       Over 5,000  |    .051113   .7148548     0.07   0.943    -1.349977    1.452203
                                   |
                 log_agency_budget |  -.1236393   .0919083    -1.35   0.179    -.3037762    .0564976
                      inst6017_nom |  -.0162414   .0116081    -1.40   0.162    -.0389928      .00651
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .2771845   .7156543     0.39   0.699    -1.125472    1.679841
                Staff: Non-Fiscal  |   .2606972    .734838     0.35   0.723    -1.179559    1.700953
Income Security & Social Services  |   .6750104   .6465859     1.04   0.297    -.5922747    1.942295
                        Education  |   .1831575   .7564553     0.24   0.809    -1.299468    1.665783
                           Health  |    .243823   .7033323     0.35   0.729    -1.134683    1.622329
                Natural Resources  |   .8700761   .6015191     1.45   0.148    -.3088796    2.049032
             Environment & Energy  |   .7902708   .6138534     1.29   0.198    -.4128597    1.993401
             Economic Development  |   .7931437   .6451527     1.23   0.219    -.4713322     2.05762
                 Criminal Justice  |   .5503779   .6525214     0.84   0.399    -.7285405    1.829296
                       Regulatory  |   1.125732   .5914521     1.90   0.057    -.0334933    2.284956
                   Transportation  |   .9685639   .6537289     1.48   0.138    -.3127212    2.249849
                            Other  |     .54782    .632791     0.87   0.387    -.6924276    1.788067
                                   |
                             state |
                               AK  |    -17.382   .4010269   -43.34   0.000      -18.168   -16.59601
                               AZ  |  -2.211708    .828193    -2.67   0.008    -3.834936   -.5884795
                               AR  |  -1.958078   .8035866    -2.44   0.015    -3.533078   -.3830768
                               CA  |  -1.337111   .8468858    -1.58   0.114    -2.996976    .3227549
                               CO  |  -1.573023   .6254014    -2.52   0.012    -2.798787   -.3472589
                               CT  |  -17.13882   .4427493   -38.71   0.000    -18.00659   -16.27105
                               DE  |  -.8178133   .6284876    -1.30   0.193    -2.049626    .4139997
                               FL  |  -2.645406   1.114893    -2.37   0.018    -4.830556   -.4602555
                               GA  |  -.8942647   .5933353    -1.51   0.132    -2.057181    .2686511
                               HI  |  -.7953776   .6226759    -1.28   0.201      -2.0158    .4250448
                               ID  |  -2.702349   .8396723    -3.22   0.001    -4.348076   -1.056622
                               IL  |  -17.06281   .4263393   -40.02   0.000    -17.89842    -16.2272
                               IN  |  -1.549528   .6588129    -2.35   0.019    -2.840778    -.258279
                               IA  |  -2.272265   .8079608    -2.81   0.005    -3.855839   -.6886904
                               KS  |  -1.855541   .7163357    -2.59   0.010    -3.259533   -.4515488
                               KY  |  -2.594847    1.10086    -2.36   0.018    -4.752494   -.4372005
                               LA  |  -2.506684   1.094392    -2.29   0.022    -4.651652    -.361716
                               ME  |  -1.293802   .7242349    -1.79   0.074    -2.713277    .1256718
                               MD  |  -16.95778   .4299576   -39.44   0.000    -17.80048   -16.11508
                               MA  |  -16.89648   .4651128   -36.33   0.000    -17.80809   -15.98488
                               MI  |  -17.20786   .4319938   -39.83   0.000    -18.05455   -16.36117
                               MN  |  -2.025008   .7825886    -2.59   0.010    -3.558854   -.4911626
                               MS  |  -1.313525   .5807307    -2.26   0.024    -2.451736   -.1753137
                               MO  |  -1.520625   .6882823    -2.21   0.027    -2.869634   -.1716167
                               MT  |  -2.581019   .8094169    -3.19   0.001    -4.167447   -.9945909
                               NE  |   -2.90273   1.095447    -2.65   0.008    -5.049767   -.7556934
                               NV  |  -2.471358   .7978933    -3.10   0.002      -4.0352   -.9075161
                               NH  |  -2.358507   .7820619    -3.02   0.003     -3.89132   -.8256941
                               NJ  |  -1.523789   .7151045    -2.13   0.033    -2.925368   -.1222097
                               NM  |  -2.012719   .8200577    -2.45   0.014    -3.620003   -.4054358
                               NY  |  -.2954766   .6818278    -0.43   0.665    -1.631835    1.040881
                               NC  |  -2.235195    .821723    -2.72   0.007    -3.845742   -.6246476
                               ND  |  -.3713697    .513924    -0.72   0.470    -1.378642    .6359028
                               OH  |  -.5233972   .5720998    -0.91   0.360    -1.644692    .5978978
                               OK  |  -2.146114   .7721902    -2.78   0.005    -3.659579   -.6326488
                               OR  |  -1.910315   .8309665    -2.30   0.022    -3.538979   -.2816504
                               PA  |  -2.256625   1.069895    -2.11   0.035    -4.353582    -.159669
                               RI  |  -.2030407   .5525241    -0.37   0.713    -1.285968    .8798866
                               SC  |  -1.725833    .747065    -2.31   0.021    -3.190053   -.2616123
                               SD  |   -1.06476   .5731035    -1.86   0.063    -2.188023    .0585017
                               TN  |  -1.864268   .8256329    -2.26   0.024    -3.482479   -.2460575
                               TX  |  -2.809823   1.108273    -2.54   0.011    -4.981998   -.6376484
                               UT  |  -2.992004   .8467377    -3.53   0.000     -4.65158   -1.332429
                               VT  |  -.3806048    .549859    -0.69   0.489    -1.458309    .6970991
                               VA  |  -17.07587   .4116536   -41.48   0.000    -17.88269   -16.26904
                               WA  |  -17.06367   .4232135   -40.32   0.000    -17.89315   -16.23418
                               WV  |  -1.214449   .6297855    -1.93   0.054    -2.448806     .019908
                               WI  |  -2.551987   1.120934    -2.28   0.023    -4.748977   -.3549971
                               WY  |  -.5809663   .5129441    -1.13   0.257    -1.586318    .4243857
                                   |
                              year |
                             1984  |  -.3529833   .3318063    -1.06   0.287    -1.003312    .2973451
                             1988  |  -.5466076   .3419461    -1.60   0.110     -1.21681    .1235945
                             1994  |  -.9709754    .415223    -2.34   0.019    -1.784798   -.1571532
                             1998  |  -.1884526   .3597602    -0.52   0.600    -.8935696    .5166643
                             2004  |   .2218176   .3538428     0.63   0.531    -.4717015    .9153367
                             2008  |   .3326727    .378509     0.88   0.379    -.4091913    1.074537
                                   |
                             _cons |   1.363435   2.207107     0.62   0.537    -2.962416    5.689286
-----------------------------------+----------------------------------------------------------------
Less_than_Monthly                  |
                      intersection |
                      White Woman  |   .0626882   .0987834     0.63   0.526    -.1309236       .2563
                     Man of Color  |   .3989689   .1364006     2.92   0.003     .1316286    .6663091
                   Woman of Color  |    .841496   .2556881     3.29   0.001     .3403565    1.342636
                                   |
                     civil_service |
                              Yes  |   .1046995   .0834871     1.25   0.210    -.0589321    .2683311
                      weekly_hours |  -.0134108   .0043622    -3.07   0.002    -.0219605   -.0048612
                               age |    .004335     .03393     0.13   0.898    -.0621665    .0708365
                             age_2 |   .0001208   .0003371     0.36   0.720    -.0005399    .0007814
                                   |
                               edu |
              High school or less  |  -.2999331   .3204737    -0.94   0.349    -.9280501    .3281838
                     Some college  |   .0756667    .163579     0.46   0.644    -.2449423    .3962757
                   Graduate study  |  -.0813737   .1182358    -0.69   0.491    -.3131116    .1503643
                  Graduate degree  |  -.0147462   .0941958    -0.16   0.876    -.1993666    .1698742
                                   |
                years_employ_state |   .0004489   .0061152     0.07   0.941    -.0115366    .0124345
               years_employ_agency |   .0032629   .0064999     0.50   0.616    -.0094767    .0160024
             years_employ_position |  -.0089868   .0080646    -1.11   0.265    -.0247931    .0068195
                                   |
                              pid5 |
                       Republican  |   .0258526   .1175972     0.22   0.826    -.2046336    .2563388
                  Lean Republican  |   .0101757   .1517425     0.07   0.947     -.287234    .3075855
                  Lean Democratic  |  -.1336683   .1486484    -0.90   0.369    -.4250137    .1576772
                       Democratic  |  -.0006256   .1100252    -0.01   0.995     -.216271    .2150198
                                   |
                       agency_size |
                           25-100  |  -.1653993   .1023684    -1.62   0.106    -.3660377    .0352391
                          101-500  |  -.1120674   .1210951    -0.93   0.355    -.3494094    .1252747
                        501-1,000  |  -.0131565   .1690233    -0.08   0.938    -.3444362    .3181231
                      1,001-5,000  |   .1536078   .1763078     0.87   0.384    -.1919491    .4991646
                       Over 5,000  |   .2603221    .258657     1.01   0.314    -.2466362    .7672805
                                   |
                 log_agency_budget |  -.0638633   .0296345    -2.16   0.031    -.1219459   -.0057807
                      inst6017_nom |   .0015447   .0043705     0.35   0.724    -.0070213    .0101107
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .2624922    .259278     1.01   0.311    -.2456834    .7706678
                Staff: Non-Fiscal  |   .8295511   .2432352     3.41   0.001     .3528189    1.306283
Income Security & Social Services  |   .5918713   .2338717     2.53   0.011     .1334912    1.050252
                        Education  |   .5197092   .2571389     2.02   0.043     .0157262    1.023692
                           Health  |   .3291332   .2479203     1.33   0.184    -.1567817     .815048
                Natural Resources  |   .3975288   .2234829     1.78   0.075    -.0404896    .8355472
             Environment & Energy  |   .7298901   .2271573     3.21   0.001     .2846699     1.17511
             Economic Development  |   .6711996   .2304796     2.91   0.004      .219468    1.122931
                 Criminal Justice  |   .4931151   .2291306     2.15   0.031     .0440274    .9422028
                       Regulatory  |   .7346697    .217439     3.38   0.001     .3084971    1.160842
                   Transportation  |   .5967835   .2475987     2.41   0.016      .111499    1.082068
                            Other  |   .7102116   .2272844     3.12   0.002     .2647425    1.155681
                                   |
                             state |
                               AK  |   -1.31132    .355384    -3.69   0.000     -2.00786   -.6147804
                               AZ  |  -.5432093   .3506522    -1.55   0.121    -1.230475    .1440564
                               AR  |   -.949569   .3453983    -2.75   0.006    -1.626537   -.2726008
                               CA  |  -.7050157   .3943962    -1.79   0.074    -1.478018    .0679866
                               CO  |  -.8768733   .3246073    -2.70   0.007    -1.513092   -.2406547
                               CT  |  -.9929925   .3917205    -2.53   0.011    -1.760751   -.2252343
                               DE  |   .0591679   .3338706     0.18   0.859    -.5952065    .7135424
                               FL  |  -.9812382   .3687251    -2.66   0.008    -1.703926   -.2585503
                               GA  |   -.957096   .3468817    -2.76   0.006    -1.636972   -.2772203
                               HI  |  -.1365303   .3458786    -0.39   0.693    -.8144399    .5413792
                               ID  |  -.6953082   .3215607    -2.16   0.031    -1.325555   -.0650609
                               IL  |  -.5392613   .3721373    -1.45   0.147    -1.268637    .1901143
                               IN  |  -.3835001   .3308107    -1.16   0.246    -1.031877    .2648768
                               IA  |   -.439688   .3175041    -1.38   0.166    -1.061984    .1826086
                               KS  |   -.769462    .342792    -2.24   0.025    -1.441322   -.0976021
                               KY  |  -.6428096   .3460086    -1.86   0.063    -1.320974    .0353548
                               LA  |  -.8101673    .361792    -2.24   0.025    -1.519267    -.101068
                               ME  |  -.6146765   .3682548    -1.67   0.095    -1.336443    .1070897
                               MD  |  -1.039373    .340726    -3.05   0.002    -1.707184   -.3715622
                               MA  |  -1.001879   .4005717    -2.50   0.012    -1.786985   -.2167728
                               MI  |  -1.001484   .3720128    -2.69   0.007    -1.730616   -.2723522
                               MN  |  -.9713413   .3535827    -2.75   0.006    -1.664351    -.278332
                               MS  |  -.8526935   .3350849    -2.54   0.011    -1.509448    -.195939
                               MO  |  -.5512543   .3358415    -1.64   0.101    -1.209492     .106983
                               MT  |  -.4442206   .3048135    -1.46   0.145    -1.041644    .1532028
                               NE  |  -.7856111   .3336318    -2.35   0.019    -1.439517   -.1317048
                               NV  |  -.8037812   .3220369    -2.50   0.013    -1.434962   -.1726005
                               NH  |  -.6096664   .3423541    -1.78   0.075    -1.280668    .0613353
                               NJ  |  -.8221497   .3389853    -2.43   0.015    -1.486549   -.1577507
                               NM  |  -.3980063   .3476264    -1.14   0.252    -1.079342    .2833289
                               NY  |  -.3333756   .4169092    -0.80   0.424    -1.150503    .4837514
                               NC  |  -.4717769   .3007777    -1.57   0.117     -1.06129    .1177366
                               ND  |   .2645103   .3117524     0.85   0.396    -.3465132    .8755339
                               OH  |  -.1942812   .3392671    -0.57   0.567    -.8592325    .4706702
                               OK  |  -.9292949   .3401438    -2.73   0.006    -1.595964   -.2626254
                               OR  |   -.652664   .3379114    -1.93   0.053    -1.314958    .0096301
                               PA  |   -.367968    .365862    -1.01   0.315    -1.085044    .3491084
                               RI  |  -.2433827   .3420467    -0.71   0.477    -.9137819    .4270165
                               SC  |   -.942476   .3729966    -2.53   0.012    -1.673536   -.2114161
                               SD  |   -.030825    .317407    -0.10   0.923    -.6529313    .5912813
                               TN  |  -.8084524   .3418863    -2.36   0.018    -1.478537   -.1383676
                               TX  |  -1.516288   .4219282    -3.59   0.000    -2.343252   -.6893239
                               UT  |  -.7032169   .3100188    -2.27   0.023    -1.310843   -.0955913
                               VT  |  -.3805173   .3398077    -1.12   0.263    -1.046528    .2854935
                               VA  |  -.3560386   .3449232    -1.03   0.302    -1.032076    .3199985
                               WA  |  -.9401179   .3345599    -2.81   0.005    -1.595843   -.2843925
                               WV  |  -.3583409   .3250471    -1.10   0.270    -.9954214    .2787397
                               WI  |  -.6692156   .3551873    -1.88   0.060     -1.36537    .0269387
                               WY  |   .1084457   .3105748     0.35   0.727    -.5002697     .717161
                                   |
                              year |
                             1984  |  -.1535848    .127593    -1.20   0.229    -.4036625    .0964929
                             1988  |  -.1986642   .1247103    -1.59   0.111    -.4430918    .0457635
                             1994  |  -.3137252   .1309515    -2.40   0.017    -.5703854   -.0570649
                             1998  |  -.2813247   .1380925    -2.04   0.042     -.551981   -.0106684
                             2004  |  -.0429875   .1402326    -0.31   0.759    -.3178383    .2318633
                             2008  |  -.4748539   .1556901    -3.05   0.002    -.7800008   -.1697069
                                   |
                             _cons |   .4206375   .9285276     0.45   0.651    -1.399243    2.240518
-----------------------------------+----------------------------------------------------------------
Monthly                            |  (base outcome)
-----------------------------------+----------------------------------------------------------------
Weekly                             |
                      intersection |
                      White Woman  |  -.0635674   .0977102    -0.65   0.515    -.2550759     .127941
                     Man of Color  |   .1686557   .1376754     1.23   0.221    -.1011832    .4384945
                   Woman of Color  |   .2451379    .273583     0.90   0.370     -.291075    .7813507
                                   |
                     civil_service |
                              Yes  |   -.227246   .0864306    -2.63   0.009    -.3966469    -.057845
                      weekly_hours |   .0172974   .0044129     3.92   0.000     .0086482    .0259466
                               age |  -.0451317   .0344832    -1.31   0.191    -.1127175     .022454
                             age_2 |   .0003839   .0003437     1.12   0.264    -.0002897    .0010576
                                   |
                               edu |
              High school or less  |  -.1317179   .3475454    -0.38   0.705    -.8128943    .5494586
                     Some college  |   .0170886   .1675959     0.10   0.919    -.3113934    .3455706
                   Graduate study  |   .0933074   .1167983     0.80   0.424     -.135613    .3222278
                  Graduate degree  |   .0807788   .0949686     0.85   0.395    -.1053563    .2669139
                                   |
                years_employ_state |   .0164477   .0058191     2.83   0.005     .0050426    .0278529
               years_employ_agency |  -.0139525   .0061445    -2.27   0.023    -.0259955   -.0019094
             years_employ_position |   .0020383   .0081932     0.25   0.804    -.0140201    .0180966
                                   |
                              pid5 |
                       Republican  |    .205439   .1181148     1.74   0.082    -.0260616    .4369397
                  Lean Republican  |  -.0426726   .1558887    -0.27   0.784    -.3482087    .2628635
                  Lean Democratic  |  -.0740156    .147195    -0.50   0.615    -.3625125    .2144812
                       Democratic  |   .1123043   .1097959     1.02   0.306    -.1028918    .3275003
                                   |
                       agency_size |
                           25-100  |  -.0759305   .1088316    -0.70   0.485    -.2892365    .1373755
                          101-500  |   .0563941   .1230885     0.46   0.647    -.1848549     .297643
                        501-1,000  |   .0519891   .1639266     0.32   0.751    -.2693011    .3732793
                      1,001-5,000  |   .0954077   .1707392     0.56   0.576    -.2392351    .4300504
                       Over 5,000  |   .4270965    .236673     1.80   0.071     -.036774     .890967
                                   |
                 log_agency_budget |   .0904967   .0285693     3.17   0.002     .0345018    .1464916
                      inst6017_nom |   .0041993   .0042507     0.99   0.323    -.0041318    .0125304
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.0049089   .2107113    -0.02   0.981    -.4178955    .4080776
                Staff: Non-Fiscal  |   -.263613   .2163654    -1.22   0.223    -.6876813    .1604553
Income Security & Social Services  |   -.530589   .1980198    -2.68   0.007    -.9187007   -.1424773
                        Education  |  -.3203872   .2182593    -1.47   0.142    -.7481677    .1073933
                           Health  |  -.6254861   .2077921    -3.01   0.003    -1.032751    -.218221
                Natural Resources  |  -.5131851   .1851676    -2.77   0.006     -.876107   -.1502632
             Environment & Energy  |   -.305679   .1927163    -1.59   0.113    -.6833959     .072038
             Economic Development  |  -.6181787   .1985161    -3.11   0.002    -1.007263   -.2290943
                 Criminal Justice  |  -.6170962   .1986032    -3.11   0.002    -1.006351    -.227841
                       Regulatory  |  -.6205626   .1867823    -3.32   0.001    -.9866492   -.2544761
                   Transportation  |  -.4887539   .2192925    -2.23   0.026    -.9185593   -.0589484
                            Other  |  -.3138327   .1977624    -1.59   0.113      -.70144    .0737745
                                   |
                             state |
                               AK  |  -.0521436   .3347322    -0.16   0.876    -.7082068    .6039195
                               AZ  |   .0081499   .3566505     0.02   0.982    -.6908723     .707172
                               AR  |  -.5043213    .354319    -1.42   0.155    -1.198774    .1901313
                               CA  |   .0085867   .3822762     0.02   0.982    -.7406609    .7578344
                               CO  |  -.3828364    .340321    -1.12   0.261    -1.049853    .2841805
                               CT  |  -.5335171   .3999083    -1.33   0.182    -1.317323    .2502887
                               DE  |   -.190367   .3693051    -0.52   0.606    -.9141917    .5334578
                               FL  |  -.1911223   .3539627    -0.54   0.589    -.8848765    .5026319
                               GA  |  -.4283839   .3530482    -1.21   0.225    -1.120346    .2635779
                               HI  |  -.5326584   .3966457    -1.34   0.179     -1.31007    .2447529
                               ID  |  -.5968756   .3562245    -1.68   0.094    -1.295063    .1013115
                               IL  |  -.3433326   .3849388    -0.89   0.372    -1.097799    .4111336
                               IN  |  -.5214903   .3681546    -1.42   0.157     -1.24306    .2000793
                               IA  |  -.1785604   .3418967    -0.52   0.601    -.8486656    .4915447
                               KS  |   .3149621   .3448997     0.91   0.361    -.3610289     .990953
                               KY  |  -.1477576   .3541898    -0.42   0.677    -.8419568    .5464417
                               LA  |  -.4211682   .3815275    -1.10   0.270    -1.168948     .326612
                               ME  |   .2570521   .3652016     0.70   0.482      -.45873    .9728341
                               MD  |  -.2100165   .3439461    -0.61   0.541    -.8841385    .4641056
                               MA  |  -.1907334   .3843389    -0.50   0.620    -.9440238     .562557
                               MI  |   .2885025   .3497436     0.82   0.409    -.3969824    .9739874
                               MN  |   .2896968   .3381055     0.86   0.392    -.3729778    .9523714
                               MS  |  -.6340582    .355842    -1.78   0.075    -1.331496    .0633793
                               MO  |   .1406957   .3453539     0.41   0.684    -.5361856     .817577
                               MT  |  -.4380853     .34185    -1.28   0.200    -1.108099    .2319284
                               NE  |   -.119526   .3443416    -0.35   0.729    -.7944231    .5553711
                               NV  |  -.6543383   .3481078    -1.88   0.060    -1.336617    .0279405
                               NH  |  -.4375454   .3763286    -1.16   0.245    -1.175136    .3000451
                               NJ  |  -.7965734   .3667594    -2.17   0.030    -1.515409   -.0777382
                               NM  |    -.19341   .3666537    -0.53   0.598     -.912038    .5252179
                               NY  |  -.2139859   .4411842    -0.49   0.628    -1.078691    .6507193
                               NC  |  -.4554941    .329603    -1.38   0.167    -1.101504     .190516
                               ND  |  -.9659642   .3989922    -2.42   0.015    -1.747975   -.1839539
                               OH  |  -.1155845   .3570645    -0.32   0.746     -.815418    .5842491
                               OK  |  -.0713525   .3409485    -0.21   0.834    -.7395993    .5968942
                               OR  |  -.1692394   .3448048    -0.49   0.624    -.8450443    .5065655
                               PA  |   .3146421   .3653845     0.86   0.389    -.4014983    1.030783
                               RI  |  -.7098197   .4038564    -1.76   0.079    -1.501364    .0817244
                               SC  |   .1946671   .3639742     0.53   0.593    -.5187093    .9080435
                               SD  |  -.7973612    .378354    -2.11   0.035    -1.538921    -.055801
                               TN  |  -.6254562   .3658834    -1.71   0.087    -1.342575    .0916621
                               TX  |   .0891644   .3560097     0.25   0.802    -.6086018    .7869306
                               UT  |   -.429913   .3336998    -1.29   0.198    -1.083953    .2241267
                               VT  |  -.0299493   .3582128    -0.08   0.933    -.7320334    .6721348
                               VA  |   -.325975   .3743848    -0.87   0.384    -1.059756    .4078057
                               WA  |  -.2365756   .3373362    -0.70   0.483    -.8977424    .4245913
                               WV  |  -.5488442   .3621414    -1.52   0.130    -1.258628    .1609399
                               WI  |   .3087392   .3436102     0.90   0.369    -.3647245    .9822029
                               WY  |  -.5336065   .3599417    -1.48   0.138    -1.239079    .1718663
                                   |
                              year |
                             1984  |  -.2725895   .1271343    -2.14   0.032    -.5217682   -.0234108
                             1988  |   .0552691    .119764     0.46   0.644     -.179464    .2900021
                             1994  |   .0493184    .126495     0.39   0.697    -.1986072     .297244
                             1998  |  -.1869589   .1346865    -1.39   0.165    -.4509397    .0770218
                             2004  |  -.3071561   .1467907    -2.09   0.036    -.5948605   -.0194517
                             2008  |   -.498279   .1519056    -3.28   0.001    -.7960085   -.2005495
                                   |
                             _cons |   .3870524   .9346089     0.41   0.679    -1.444747    2.218852
-----------------------------------+----------------------------------------------------------------
Daily                              |
                      intersection |
                      White Woman  |   .0068487   .1542056     0.04   0.965    -.2953888    .3090862
                     Man of Color  |  -.3722072   .2583345    -1.44   0.150    -.8785335    .1341191
                   Woman of Color  |  -.1677195   .4329275    -0.39   0.698    -1.016242    .6808029
                                   |
                     civil_service |
                              Yes  |   -.320201   .1461527    -2.19   0.028    -.6066551    -.033747
                      weekly_hours |   .0500662    .006164     8.12   0.000      .037985    .0621474
                               age |  -.0741437   .0548545    -1.35   0.176    -.1816566    .0333691
                             age_2 |    .000714   .0005552     1.29   0.198    -.0003743    .0018023
                                   |
                               edu |
              High school or less  |   .0920534   .4781983     0.19   0.847     -.845198    1.029305
                     Some college  |   -.157866   .2619498    -0.60   0.547    -.6712783    .3555462
                   Graduate study  |   .1397977   .1822205     0.77   0.443    -.2173479    .4969433
                  Graduate degree  |   .0428139   .1495429     0.29   0.775    -.2502849    .3359126
                                   |
                years_employ_state |   .0217749   .0089812     2.42   0.015     .0041721    .0393778
               years_employ_agency |  -.0045219   .0096258    -0.47   0.639    -.0233881    .0143442
             years_employ_position |  -.0097134   .0127573    -0.76   0.446    -.0347171    .0152904
                                   |
                              pid5 |
                       Republican  |   .0258259   .1789138     0.14   0.885    -.3248387    .3764904
                  Lean Republican  |   .1202689   .2377941     0.51   0.613    -.3457991    .5863368
                  Lean Democratic  |  -.1732844   .2321036    -0.75   0.455     -.628199    .2816303
                       Democratic  |  -.0651125   .1661639    -0.39   0.695    -.3907877    .2605627
                                   |
                       agency_size |
                           25-100  |  -.1192853   .1776797    -0.67   0.502    -.4675311    .2289606
                          101-500  |   -.120995   .2026253    -0.60   0.550    -.5181334    .2761434
                        501-1,000  |   .1680854   .2591996     0.65   0.517    -.3399365    .6761074
                      1,001-5,000  |   .1961872   .2776196     0.71   0.480    -.3479371    .7403116
                       Over 5,000  |   .5775475   .3465156     1.67   0.096    -.1016105    1.256706
                                   |
                 log_agency_budget |   .0018437   .0469726     0.04   0.969    -.0902209    .0939083
                      inst6017_nom |   .0132911   .0065774     2.02   0.043     .0003997    .0261826
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.0445147   .2706302    -0.16   0.869    -.5749403    .4859108
                Staff: Non-Fiscal  |  -.7828082   .3114057    -2.51   0.012    -1.393152   -.1724642
Income Security & Social Services  |  -1.060901   .2757849    -3.85   0.000     -1.60143   -.5203728
                        Education  |  -.7995741    .300724    -2.66   0.008    -1.388982    -.210166
                           Health  |  -1.514294   .3216315    -4.71   0.000     -2.14468   -.8839079
                Natural Resources  |  -1.397526   .2694673    -5.19   0.000    -1.925672   -.8693797
             Environment & Energy  |  -1.772171   .3251389    -5.45   0.000    -2.409432   -1.134911
             Economic Development  |  -1.599837    .312333    -5.12   0.000    -2.211999   -.9876758
                 Criminal Justice  |  -1.210008    .284122    -4.26   0.000    -1.766877   -.6531386
                       Regulatory  |  -1.325939   .2681968    -4.94   0.000    -1.851595   -.8002831
                   Transportation  |  -.6589169   .2954316    -2.23   0.026    -1.237952   -.0798816
                            Other  |  -1.034714    .288691    -3.58   0.000    -1.600538   -.4688901
                                   |
                             state |
                               AK  |   .9732103   .5302237     1.84   0.066     -.066009     2.01243
                               AZ  |   .7223032   .5682786     1.27   0.204    -.3915024    1.836109
                               AR  |   .1795144   .5576671     0.32   0.748     -.913493    1.272522
                               CA  |   .7704642   .5763369     1.34   0.181    -.3591353    1.900064
                               CO  |   .0078439   .5630296     0.01   0.989    -1.095674    1.111362
                               CT  |  -.5889526   .7529991    -0.78   0.434    -2.064804    .8868986
                               DE  |   .1207971   .6097899     0.20   0.843    -1.074369    1.315963
                               FL  |   .1666113   .5819218     0.29   0.775    -.9739345    1.307157
                               GA  |  -.2333873   .6008083    -0.39   0.698     -1.41095    .9441753
                               HI  |  -.2725003   .6809586    -0.40   0.689    -1.607155    1.062154
                               ID  |  -.0712201   .5854701    -0.12   0.903     -1.21872     1.07628
                               IL  |   .0057843   .6449253     0.01   0.993    -1.258246    1.269815
                               IN  |  -.7309527    .713329    -1.02   0.306    -2.129052    .6671465
                               IA  |  -.4262557   .6220062    -0.69   0.493    -1.645365     .792854
                               KS  |    .754385   .5622151     1.34   0.180    -.3475363    1.856306
                               KY  |  -.5260781   .6709901    -0.78   0.433    -1.841195    .7890383
                               LA  |   .6163518   .5763808     1.07   0.285    -.5133338    1.746037
                               ME  |   .2292252   .6305081     0.36   0.716    -1.006548    1.464998
                               MD  |  -.4325636   .6173191    -0.70   0.483    -1.642487    .7773595
                               MA  |  -.0008549   .6192637    -0.00   0.999    -1.214589     1.21288
                               MI  |   1.528483   .5285886     2.89   0.004     .4924686    2.564498
                               MN  |   .6622914   .5426697     1.22   0.222    -.4013217    1.725904
                               MS  |   -.320134   .5916961    -0.54   0.588    -1.479837    .8395691
                               MO  |   .1191898   .5767238     0.21   0.836    -1.011168    1.249548
                               MT  |  -.4341721   .5977017    -0.73   0.468    -1.605646    .7373017
                               NE  |   .5268382   .5532727     0.95   0.341    -.5575563    1.611233
                               NV  |  -.7932352   .6748831    -1.18   0.240    -2.115982    .5295113
                               NH  |   1.072824   .5533563     1.94   0.053    -.0117348    2.157382
                               NJ  |  -.5612685   .6319616    -0.89   0.374    -1.799891    .6773535
                               NM  |  -.1863795    .649861    -0.29   0.774    -1.460084    1.087325
                               NY  |   .3307616   .6631267     0.50   0.618    -.9689428    1.630466
                               NC  |  -.3425816   .5676874    -0.60   0.546    -1.455228    .7700652
                               ND  |  -1.119298   .7640788    -1.46   0.143    -2.616865    .3782685
                               OH  |   .7718163   .5560972     1.39   0.165    -.3181142    1.861747
                               OK  |   .9093958   .5365185     1.69   0.090    -.1421612    1.960953
                               OR  |  -.1872395   .6001053    -0.31   0.755    -1.363424    .9889453
                               PA  |   .7967847   .5673803     1.40   0.160    -.3152602     1.90883
                               RI  |  -.8485965   .7793617    -1.09   0.276    -2.376117    .6789243
                               SC  |    1.25733   .5458636     2.30   0.021     .1874568    2.327203
                               SD  |  -1.627292   .8728264    -1.86   0.062       -3.338    .0834167
                               TN  |   .0866158   .5868086     0.15   0.883    -1.063508     1.23674
                               TX  |   1.023749   .5511096     1.86   0.063    -.0564062    2.103904
                               UT  |  -1.053981   .6978399    -1.51   0.131    -2.421722    .3137605
                               VT  |  -.3378044   .6376001    -0.53   0.596    -1.587478    .9118688
                               VA  |  -.6598238   .7242573    -0.91   0.362    -2.079342    .7596945
                               WA  |  -1.486636   .7618303    -1.95   0.051    -2.979796    .0065245
                               WV  |  -.5830665   .6398073    -0.91   0.362    -1.837066    .6709328
                               WI  |   .8507111   .5350239     1.59   0.112    -.1979165    1.899339
                               WY  |   -1.10439   .7457021    -1.48   0.139     -2.56594    .3571591
                                   |
                              year |
                             1984  |  -.3009075     .18494    -1.63   0.104    -.6633833    .0615683
                             1988  |  -.1114991   .1748479    -0.64   0.524    -.4541946    .2311964
                             1994  |  -.1625426   .1895463    -0.86   0.391    -.5340465    .2089614
                             1998  |  -.7460118   .2184254    -3.42   0.001    -1.174118   -.3179058
                             2004  |  -1.305247   .2691565    -4.85   0.000    -1.832784   -.7777098
                             2008  |  -.7790626   .2507829    -3.11   0.002    -1.270588   -.2875372
                                   |
                             _cons |  -1.726537   1.464539    -1.18   0.238     -4.59698    1.143907
----------------------------------------------------------------------------------------------------

. est sto mlogit4

. 
.  esttab mlogit4 using Table_B11.rtf  ,starlevels(+ 0.10 * 0.05 ** 0.01) cells(b(star fmt(3)) se(par fmt(3))
> ) ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Legis. Staff" ) 
(output written to Table_B11.rtf)

. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B12 ******
. mlogit d_15a i.intersection i.reve_1a i.reve_1b i.civil_service weekly_hours age age_2 b3.edu years_employ_
> state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fun
> cat13 i.state i.year , base(2) r 

Iteration 0:   log pseudolikelihood = -6426.3351  
Iteration 1:   log pseudolikelihood =  -5817.893  
Iteration 2:   log pseudolikelihood = -5633.8314  
Iteration 3:   log pseudolikelihood = -5608.1216  
Iteration 4:   log pseudolikelihood = -5607.4185  
Iteration 5:   log pseudolikelihood = -5607.3066  
Iteration 6:   log pseudolikelihood = -5607.2866  
Iteration 7:   log pseudolikelihood = -5607.2845  
Iteration 8:   log pseudolikelihood = -5607.2841  
Iteration 9:   log pseudolikelihood =  -5607.284  
Iteration 10:  log pseudolikelihood =  -5607.284  

Multinomial logistic regression                 Number of obs     =      6,224
                                                Wald chi2(300)    =    8732.53
                                                Prob > chi2       =     0.0000
Log pseudolikelihood =  -5607.284               Pseudo R2         =     0.1275

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_15a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
None                               |
                      intersection |
                      White Woman  |   .5360779   .2380147     2.25   0.024     .0695776    1.002578
                     Man of Color  |   .1765105   .3750297     0.47   0.638    -.5585342    .9115552
                   Woman of Color  |   1.315245   .5554684     2.37   0.018     .2265468    2.403943
                                   |
                           reve_1a |
                Less than Monthly  |  -.3892041   .2176085    -1.79   0.074    -.8157088    .0373007
                          Monthly  |  -1.132111   .3512917    -3.22   0.001     -1.82063   -.4435922
                           Weekly  |  -1.016159   .4498426    -2.26   0.024    -1.897834   -.1344837
                            Daily  |  -.2787123    1.03313    -0.27   0.787    -2.303611    1.746186
                                   |
                           reve_1b |
                Less than Monthly  |  -.6930584   .3565428    -1.94   0.052    -1.391869    .0057526
                          Monthly  |  -1.126181   .3885374    -2.90   0.004      -1.8877   -.3646613
                           Weekly  |  -.9879618   .4209471    -2.35   0.019    -1.813003   -.1629207
                            Daily  |  -1.661484   .5841965    -2.84   0.004    -2.806488   -.5164802
                                   |
                     civil_service |
                              Yes  |  -.4342787   .2282427    -1.90   0.057    -.8816261    .0130687
                      weekly_hours |   .0045991   .0107935     0.43   0.670    -.0165557    .0257539
                               age |   .1760185   .0786906     2.24   0.025     .0217877    .3302493
                             age_2 |  -.0015349   .0007601    -2.02   0.043    -.0030247   -.0000452
                                   |
                               edu |
              High school or less  |  -.2135218   .8122331    -0.26   0.793    -1.805469    1.378426
                     Some college  |   .0369786   .3468586     0.11   0.915    -.6428517    .7168089
                   Graduate study  |  -.4825862   .2924564    -1.65   0.099     -1.05579    .0906178
                  Graduate degree  |  -.3433321   .2124589    -1.62   0.106    -.7597438    .0730796
                                   |
                years_employ_state |  -.0150114   .0152969    -0.98   0.326    -.0449929      .01497
               years_employ_agency |   .0080784   .0163598     0.49   0.621    -.0239862    .0401431
             years_employ_position |   .0239077   .0165336     1.45   0.148    -.0084977     .056313
                                   |
                              pid5 |
                       Republican  |   .2999689   .2913322     1.03   0.303    -.2710317    .8709694
                  Lean Republican  |   .5131904   .3833987     1.34   0.181    -.2382571    1.264638
                  Lean Democratic  |  -.3668292   .4265194    -0.86   0.390    -1.202792    .4691335
                       Democratic  |   .2799904   .2587927     1.08   0.279    -.2272339    .7872147
                                   |
                       agency_size |
                           25-100  |  -.1622501   .2307254    -0.70   0.482    -.6144636    .2899633
                          101-500  |  -.2592066   .3068772    -0.84   0.398    -.8606748    .3422616
                        501-1,000  |   .0446024   .4369793     0.10   0.919    -.8118613    .9010662
                      1,001-5,000  |   .1861202   .5233571     0.36   0.722    -.8396409    1.211881
                       Over 5,000  |  -.8963549    1.07418    -0.83   0.404    -3.001708    1.208999
                                   |
                 log_agency_budget |  -.2010438   .0900876    -2.23   0.026    -.3776123   -.0244753
                      inst6017_nom |  -.0115827   .0108607    -1.07   0.286    -.0328693     .009704
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -1.737958   .5360036    -3.24   0.001    -2.788505     -.68741
                Staff: Non-Fiscal  |  -2.900281   .6482178    -4.47   0.000    -4.170764   -1.629797
Income Security & Social Services  |  -3.022409   .5308449    -5.69   0.000    -4.062846   -1.981973
                        Education  |  -2.986527   .6806498    -4.39   0.000    -4.320576   -1.652478
                           Health  |  -3.160196   .6521811    -4.85   0.000    -4.438447   -1.881945
                Natural Resources  |  -2.255116   .3687479    -6.12   0.000    -2.977848   -1.532383
             Environment & Energy  |  -2.445066    .420848    -5.81   0.000    -3.269913   -1.620219
             Economic Development  |  -1.520428   .4287555    -3.55   0.000    -2.360773   -.6800821
                 Criminal Justice  |   -2.23217   .4377804    -5.10   0.000    -3.090204   -1.374137
                       Regulatory  |  -1.463979   .3006242    -4.87   0.000    -2.053192   -.8747669
                   Transportation  |  -1.792556   .4552942    -3.94   0.000    -2.684916   -.9001955
                            Other  |  -1.392331   .3370168    -4.13   0.000    -2.052872   -.7317898
                                   |
                             state |
                               AK  |  -1.347304   .9070813    -1.49   0.137     -3.12515    .4305431
                               AZ  |  -.0415648   .6454075    -0.06   0.949     -1.30654    1.223411
                               AR  |   .1702323   .7807184     0.22   0.827    -1.359948    1.700412
                               CA  |  -.4143093    .781422    -0.53   0.596    -1.945868     1.11725
                               CO  |  -.3305906   .6709186    -0.49   0.622    -1.645567    .9843856
                               CT  |  -.5044635   1.033211    -0.49   0.625    -2.529519    1.520592
                               DE  |  -1.354131   .8989624    -1.51   0.132    -3.116065    .4078029
                               FL  |   .0769998   .7206821     0.11   0.915    -1.335511    1.489511
                               GA  |  -1.838969    1.15251    -1.60   0.111    -4.097847    .4199081
                               HI  |  -.6890102   .8128356    -0.85   0.397    -2.282139    .9041182
                               ID  |  -1.623282   .8495122    -1.91   0.056    -3.288295    .0417313
                               IL  |   .3579195   .7634901     0.47   0.639    -1.138494    1.854333
                               IN  |    -1.3126   .9693726    -1.35   0.176    -3.212535    .5873356
                               IA  |   -.386835   .7000145    -0.55   0.581    -1.758838    .9851682
                               KS  |  -.4604025   .7602163    -0.61   0.545    -1.950399    1.029594
                               KY  |  -1.123347   .9548034    -1.18   0.239    -2.994727    .7480334
                               LA  |   .2269117   .7184592     0.32   0.752    -1.181243    1.635066
                               ME  |  -.5991135   .8184922    -0.73   0.464    -2.203329    1.005102
                               MD  |  -1.100569   .8923239    -1.23   0.217    -2.849492    .6483538
                               MA  |   -14.3255   .5966764   -24.01   0.000    -15.49496   -13.15603
                               MI  |  -2.046387   1.171869    -1.75   0.081    -4.343207    .2504337
                               MN  |  -1.800138   .8927144    -2.02   0.044    -3.549826   -.0504495
                               MS  |    .400091   .6353849     0.63   0.529    -.8452405    1.645422
                               MO  |  -.1489689   .6971997    -0.21   0.831    -1.515455    1.217517
                               MT  |   -.364088   .6778008    -0.54   0.591    -1.692553    .9643772
                               NE  |  -1.836096   .9736637    -1.89   0.059    -3.744441    .0722502
                               NV  |  -.8522754   .8270976    -1.03   0.303    -2.473357    .7688061
                               NH  |  -1.183229   .7646697    -1.55   0.122    -2.681955    .3154957
                               NJ  |  -1.106548   .9474331    -1.17   0.243    -2.963483    .7503865
                               NM  |  -.5460041   .7018701    -0.78   0.437    -1.921644    .8296361
                               NY  |    -13.546   .7113314   -19.04   0.000    -14.94019   -12.15182
                               NC  |  -.2079761   .6424925    -0.32   0.746    -1.467238    1.051286
                               ND  |  -1.625453   .8808438    -1.85   0.065    -3.351875    .1009692
                               OH  |  -.5159374   .7889992    -0.65   0.513    -2.062348    1.030473
                               OK  |  -1.238199   .7329225    -1.69   0.091    -2.674701    .1983025
                               OR  |  -.7748065   .7032489    -1.10   0.271    -2.153149     .603536
                               PA  |  -1.007765   .7829491    -1.29   0.198    -2.542317    .5267874
                               RI  |  -.0479754   .7706491    -0.06   0.950     -1.55842    1.462469
                               SC  |  -.1638048   .6864397    -0.24   0.811    -1.509202    1.181592
                               SD  |  -.8089923   .8263726    -0.98   0.328    -2.428653    .8106683
                               TN  |  -.4251328    .760498    -0.56   0.576    -1.915682    1.065416
                               TX  |  -.2652645   .6696404    -0.40   0.692    -1.577735    1.047207
                               UT  |  -2.838097    1.09183    -2.60   0.009    -4.978044   -.6981506
                               VT  |  -1.326695   .8959999    -1.48   0.139    -3.082822    .4294327
                               VA  |  -1.816576    1.10376    -1.65   0.100    -3.979905    .3467538
                               WA  |  -.7766234   .8343336    -0.93   0.352    -2.411887    .8586404
                               WV  |  -.3527451   .7770141    -0.45   0.650    -1.875665    1.170174
                               WI  |  -2.345367   1.196994    -1.96   0.050    -4.691431    .0006978
                               WY  |  -.4505381   .6906505    -0.65   0.514    -1.804188     .903112
                                   |
                              year |
                             1984  |  -.9333281   .2882041    -3.24   0.001    -1.498198   -.3684585
                             1988  |  -.6588702   .2678961    -2.46   0.014    -1.183937   -.1338035
                             1994  |  -1.106053   .3034236    -3.65   0.000    -1.700752   -.5113535
                             1998  |  -1.088553   .3380704    -3.22   0.001    -1.751158   -.4259467
                             2004  |  -1.992288   .4118027    -4.84   0.000    -2.799407    -1.18517
                             2008  |  -1.392622   .3618436    -3.85   0.000    -2.101822   -.6834214
                                   |
                             _cons |  -1.235486   2.204752    -0.56   0.575    -5.556722    3.085749
-----------------------------------+----------------------------------------------------------------
Slight                             |
                      intersection |
                      White Woman  |  -.1244154   .1370101    -0.91   0.364    -.3929502    .1441195
                     Man of Color  |  -.0690288   .2036458    -0.34   0.735    -.4681672    .3301096
                   Woman of Color  |  -.1505044   .4337525    -0.35   0.729    -1.000644    .6996349
                                   |
                           reve_1a |
                Less than Monthly  |   -.320218   .1300346    -2.46   0.014     -.575081   -.0653549
                          Monthly  |  -.5752435    .180493    -3.19   0.001    -.9290032   -.2214838
                           Weekly  |  -.6114384   .2548625    -2.40   0.016     -1.11096    -.111917
                            Daily  |  -1.239098   1.112497    -1.11   0.265    -3.419552    .9413564
                                   |
                           reve_1b |
                Less than Monthly  |  -.2289262   .2657588    -0.86   0.389    -.7498039    .2919515
                          Monthly  |  -.1937895   .2790448    -0.69   0.487    -.7407073    .3531282
                           Weekly  |  -.5741121   .2936736    -1.95   0.051    -1.149702    .0014775
                            Daily  |  -1.112509   .3572062    -3.11   0.002     -1.81262   -.4123978
                                   |
                     civil_service |
                              Yes  |  -.4065663   .1212776    -3.35   0.001     -.644266   -.1688666
                      weekly_hours |   .0022236   .0060486     0.37   0.713    -.0096314    .0140786
                               age |   .0161106   .0423198     0.38   0.703    -.0668346    .0990559
                             age_2 |  -.0000902   .0004119    -0.22   0.827    -.0008976    .0007171
                                   |
                               edu |
              High school or less  |    .326055   .4196572     0.78   0.437    -.4964581    1.148568
                     Some college  |  -.0139846   .2212553    -0.06   0.950    -.4476371    .4196678
                   Graduate study  |  -.3901949   .1726367    -2.26   0.024    -.7285566   -.0518333
                  Graduate degree  |  -.0101653   .1274677    -0.08   0.936    -.2599974    .2396669
                                   |
                years_employ_state |  -.0011604   .0082174    -0.14   0.888    -.0172663    .0149455
               years_employ_agency |   .0111914   .0085624     1.31   0.191    -.0055907    .0279735
             years_employ_position |  -.0035318   .0100019    -0.35   0.724    -.0231351    .0160716
                                   |
                              pid5 |
                       Republican  |   .0662957   .1590864     0.42   0.677     -.245508    .3780994
                  Lean Republican  |  -.0026297   .2105194    -0.01   0.990    -.4152401    .4099807
                  Lean Democratic  |   .0363734   .1951918     0.19   0.852    -.3461956    .4189423
                       Democratic  |   .2266653   .1477986     1.53   0.125    -.0630146    .5163452
                                   |
                       agency_size |
                           25-100  |   .0709697   .1452714     0.49   0.625     -.213757    .3556965
                          101-500  |   .0657885     .16653     0.40   0.693    -.2606043    .3921812
                        501-1,000  |  -.0660082   .2264825    -0.29   0.771    -.5099057    .3778893
                      1,001-5,000  |   .0537025   .2368394     0.23   0.821    -.4104941    .5178991
                       Over 5,000  |   .3279857   .3282187     1.00   0.318    -.3153111    .9712826
                                   |
                 log_agency_budget |  -.0116715   .0393959    -0.30   0.767     -.088886    .0655429
                      inst6017_nom |  -.0073209   .0056354    -1.30   0.194     -.018366    .0037243
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -1.323209   .3176607    -4.17   0.000    -1.945813   -.7006057
                Staff: Non-Fiscal  |  -2.018356   .3530272    -5.72   0.000    -2.710277   -1.326436
Income Security & Social Services  |  -1.441268   .2397236    -6.01   0.000    -1.911117   -.9714179
                        Education  |  -1.261573    .252199    -5.00   0.000    -1.755874   -.7672715
                           Health  |  -1.537364   .2627036    -5.85   0.000    -2.052253   -1.022474
                Natural Resources  |  -1.164692   .2114254    -5.51   0.000    -1.579079   -.7503062
             Environment & Energy  |  -1.804432   .2552939    -7.07   0.000    -2.304799   -1.304065
             Economic Development  |  -1.152004   .2603454    -4.42   0.000    -1.662271   -.6417363
                 Criminal Justice  |  -1.680825   .2536687    -6.63   0.000    -2.178007   -1.183643
                       Regulatory  |  -1.236555   .2131424    -5.80   0.000    -1.654306   -.8188034
                   Transportation  |  -1.311238   .2800992    -4.68   0.000    -1.860222   -.7622534
                            Other  |  -.8249959   .2274758    -3.63   0.000     -1.27084   -.3791516
                                   |
                             state |
                               AK  |  -1.483529   .4723235    -3.14   0.002    -2.409266   -.5577923
                               AZ  |  -1.005744   .4451025    -2.26   0.024    -1.878129   -.1333591
                               AR  |  -.5655423   .4631172    -1.22   0.222    -1.473235    .3421508
                               CA  |  -.6300462   .4801385    -1.31   0.189      -1.5711    .3110079
                               CO  |  -.5516073   .3809789    -1.45   0.148    -1.298312    .1950976
                               CT  |  -.5493814   .5366812    -1.02   0.306    -1.601257    .5024944
                               DE  |  -1.526007   .4670434    -3.27   0.001    -2.441395   -.6106188
                               FL  |  -.7828135   .4369511    -1.79   0.073    -1.639222    .0735949
                               GA  |  -.9115887   .4016064    -2.27   0.023    -1.698723   -.1244546
                               HI  |  -1.046551   .4909459    -2.13   0.033    -2.008787   -.0843146
                               ID  |  -.7778768   .4031248    -1.93   0.054    -1.567987    .0122333
                               IL  |  -.6451622   .5101148    -1.26   0.206    -1.644969    .3546443
                               IN  |  -1.121692   .4629269    -2.42   0.015    -2.029012    -.214372
                               IA  |  -.3982405   .3840231    -1.04   0.300    -1.150912    .3544309
                               KS  |  -.7520301   .4331698    -1.74   0.083    -1.601027    .0969671
                               KY  |  -.9604468   .4423322    -2.17   0.030    -1.827402   -.0934916
                               LA  |  -.8688794   .4533984    -1.92   0.055    -1.757524    .0197652
                               ME  |  -1.068333   .4876534    -2.19   0.028    -2.024117   -.1125504
                               MD  |   -.537483   .4370704    -1.23   0.219    -1.394125    .3191592
                               MA  |  -.8663753    .431625    -2.01   0.045    -1.712345   -.0204059
                               MI  |  -1.999582   .5275705    -3.79   0.000    -3.033601   -.9655628
                               MN  |  -1.475829   .4174484    -3.54   0.000    -2.294013   -.6576455
                               MS  |   .1864559   .3615473     0.52   0.606    -.5221639    .8950757
                               MO  |  -.1425511    .391656    -0.36   0.716    -.9101828    .6250806
                               MT  |  -.6772274   .3791073    -1.79   0.074    -1.420264    .0658093
                               NE  |    -.92776   .4181445    -2.22   0.027    -1.747308   -.1082118
                               NV  |    -.83371   .4206108    -1.98   0.047    -1.658092   -.0093281
                               NH  |  -1.547887   .4803243    -3.22   0.001    -2.489305   -.6064683
                               NJ  |  -1.111457    .474833    -2.34   0.019    -2.042113   -.1808019
                               NM  |   -.893759   .4634042    -1.93   0.054    -1.802014    .0144965
                               NY  |    .127074    .632464     0.20   0.841    -1.112533    1.366681
                               NC  |  -.9604408   .3674702    -2.61   0.009    -1.680669   -.2402124
                               ND  |  -.5329179   .3862751    -1.38   0.168    -1.290003    .2241673
                               OH  |  -.8084802    .423635    -1.91   0.056    -1.638789    .0218292
                               OK  |  -.8150207   .3673829    -2.22   0.027    -1.535078   -.0949635
                               OR  |  -1.246407   .4240276    -2.94   0.003    -2.077485   -.4153278
                               PA  |  -1.283718   .4329767    -2.96   0.003    -2.132337   -.4350996
                               RI  |  -1.451439   .5636292    -2.58   0.010    -2.556132   -.3467461
                               SC  |  -.6670509   .3824544    -1.74   0.081    -1.416648     .082546
                               SD  |  -.5817836   .4250427    -1.37   0.171    -1.414852    .2512849
                               TN  |  -1.094796   .4401141    -2.49   0.013    -1.957404   -.2321878
                               TX  |  -.1079519   .3665898    -0.29   0.768    -.8264546    .6105509
                               UT  |  -1.316971   .4017376    -3.28   0.001    -2.104362   -.5295797
                               VT  |  -1.264989   .4764792    -2.65   0.008    -2.198871    -.331107
                               VA  |  -.9970931   .4566282    -2.18   0.029    -1.892068   -.1021183
                               WA  |  -.2391015   .3969452    -0.60   0.547      -1.0171    .5388968
                               WV  |  -.3638671   .3982963    -0.91   0.361    -1.144514    .4167793
                               WI  |  -1.159213    .461268    -2.51   0.012    -2.063282   -.2551448
                               WY  |   -.764481   .3852591    -1.98   0.047    -1.519575    -.009387
                                   |
                              year |
                             1984  |  -.3471597   .1699013    -2.04   0.041    -.6801602   -.0141592
                             1988  |  -.3214465   .1610488    -2.00   0.046    -.6370963   -.0057966
                             1994  |   -.507394    .179135    -2.83   0.005    -.8584921   -.1562958
                             1998  |  -.6983358   .1925989    -3.63   0.000    -1.075823   -.3208489
                             2004  |  -.1963369   .1828479    -1.07   0.283    -.5547121    .1620383
                             2008  |  -.5916977   .2109102    -2.81   0.005    -1.005074   -.1783213
                                   |
                             _cons |   1.974156    1.19199     1.66   0.098    -.3621014    4.310414
-----------------------------------+----------------------------------------------------------------
Moderate                           |  (base outcome)
-----------------------------------+----------------------------------------------------------------
High                               |
                      intersection |
                      White Woman  |   -.121992   .0911322    -1.34   0.181    -.3006078    .0566237
                     Man of Color  |    .323073   .1357302     2.38   0.017     .0570467    .5890993
                   Woman of Color  |    .765906   .2653507     2.89   0.004     .2458281    1.285984
                                   |
                           reve_1a |
                Less than Monthly  |   .0835134   .0980686     0.85   0.394    -.1086977    .2757244
                          Monthly  |  -.0640376   .1253111    -0.51   0.609    -.3096428    .1815676
                           Weekly  |   .2805704   .1593888     1.76   0.078     -.031826    .5929668
                            Daily  |   1.102212   .3978796     2.77   0.006     .3223826    1.882042
                                   |
                           reve_1b |
                Less than Monthly  |   -.013256   .2260579    -0.06   0.953    -.4563213    .4298092
                          Monthly  |   .1842916   .2345692     0.79   0.432    -.2754555    .6440387
                           Weekly  |   .5613461   .2394465     2.34   0.019     .0920396    1.030653
                            Daily  |   .9635402   .2599914     3.71   0.000     .4539663    1.473114
                                   |
                     civil_service |
                              Yes  |  -.0370555   .0801017    -0.46   0.644     -.194052     .119941
                      weekly_hours |  -.0061407   .0042164    -1.46   0.145    -.0144046    .0021233
                               age |    .052475   .0313686     1.67   0.094    -.0090064    .1139564
                             age_2 |   -.000557    .000311    -1.79   0.073    -.0011667    .0000526
                                   |
                               edu |
              High school or less  |   .0274543   .3095687     0.09   0.929    -.5792893    .6341979
                     Some college  |  -.2492471   .1587371    -1.57   0.116    -.5603661    .0618718
                   Graduate study  |  -.0542528   .1121905    -0.48   0.629    -.2741422    .1656366
                  Graduate degree  |  -.1937833   .0910025    -2.13   0.033    -.3721449   -.0154216
                                   |
                years_employ_state |  -.0026675   .0055328    -0.48   0.630    -.0135115    .0081766
               years_employ_agency |   .0021048   .0059085     0.36   0.722    -.0094757    .0136853
             years_employ_position |  -.0223944   .0078013    -2.87   0.004    -.0376848   -.0071041
                                   |
                              pid5 |
                       Republican  |   .0324095   .1097481     0.30   0.768    -.1826929    .2475119
                  Lean Republican  |  -.0083629   .1425446    -0.06   0.953    -.2877451    .2710194
                  Lean Democratic  |  -.1158042   .1336213    -0.87   0.386    -.3776972    .1460887
                       Democratic  |   .0084769   .1014248     0.08   0.933    -.1903121     .207266
                                   |
                       agency_size |
                           25-100  |   .0826269   .1007672     0.82   0.412    -.1148731    .2801269
                          101-500  |  -.1335357    .115056    -1.16   0.246    -.3590412    .0919699
                        501-1,000  |  -.1518647   .1544493    -0.98   0.325    -.4545798    .1508504
                      1,001-5,000  |  -.2288696   .1606845    -1.42   0.154    -.5438054    .0860661
                       Over 5,000  |  -.0725249   .2280211    -0.32   0.750    -.5194382    .3743883
                                   |
                 log_agency_budget |   .0363993   .0275672     1.32   0.187    -.0176313    .0904299
                      inst6017_nom |  -.0063214   .0040361    -1.57   0.117     -.014232    .0015893
                                   |
                          funcat13 |
                    Staff: Fiscal  |   1.887985   .2439234     7.74   0.000     1.409904    2.366066
                Staff: Non-Fiscal  |   1.971918   .2462722     8.01   0.000     1.489233    2.454603
Income Security & Social Services  |   1.138969    .223031     5.11   0.000     .7018358    1.576101
                        Education  |   .9691382   .2375867     4.08   0.000     .5034767      1.4348
                           Health  |   1.034102   .2327046     4.44   0.000     .5780094    1.490195
                Natural Resources  |   1.174309   .2130288     5.51   0.000     .7567805    1.591838
             Environment & Energy  |   1.589871   .2191167     7.26   0.000     1.160411    2.019332
             Economic Development  |    1.60989    .228009     7.06   0.000        1.163    2.056779
                 Criminal Justice  |    1.39093   .2216173     6.28   0.000     .9565683    1.825292
                       Regulatory  |   1.246223    .213336     5.84   0.000     .8280919    1.664354
                   Transportation  |   1.707316   .2420237     7.05   0.000     1.232958    2.181674
                            Other  |   1.486411   .2228882     6.67   0.000     1.049558    1.923264
                                   |
                             state |
                               AK  |    .522408    .301818     1.73   0.083    -.0691445     1.11396
                               AZ  |   .2620812   .3265161     0.80   0.422    -.3778786    .9020411
                               AR  |   .7953426   .3326424     2.39   0.017     .1433755     1.44731
                               CA  |   1.311593   .3749642     3.50   0.000     .5766767    2.046509
                               CO  |   .0012738   .3052516     0.00   0.997    -.5970083     .599556
                               CT  |    .907866   .3830233     2.37   0.018     .1571542    1.658578
                               DE  |   .6758952   .3067682     2.20   0.028     .0746406     1.27715
                               FL  |   .5236795   .3275218     1.60   0.110    -.1182514     1.16561
                               GA  |   .5463514   .3172145     1.72   0.085    -.0753776     1.16808
                               HI  |   .7222591   .3303203     2.19   0.029     .0748432    1.369675
                               ID  |   .0894993   .3126837     0.29   0.775    -.5233494     .702348
                               IL  |   1.022963   .3802259     2.69   0.007     .2777344    1.768192
                               IN  |   .5338084   .3216137     1.66   0.097    -.0965429     1.16416
                               IA  |   .6819733   .3098985     2.20   0.028     .0745833    1.289363
                               KS  |   .8655828    .319039     2.71   0.007     .2402778    1.490888
                               KY  |   .7039137   .3248785     2.17   0.030     .0671636    1.340664
                               LA  |   .5897079   .3503447     1.68   0.092    -.0969551    1.276371
                               ME  |   .6884522   .3316146     2.08   0.038     .0384995    1.338405
                               MD  |   1.069318   .3210947     3.33   0.001     .4399839    1.698652
                               MA  |   .2283825   .3402193     0.67   0.502    -.4384351    .8952001
                               MI  |   .5394826   .3027121     1.78   0.075    -.0538222    1.132787
                               MN  |   .2361608   .2917557     0.81   0.418    -.3356698    .8079914
                               MS  |  -.2808467   .3352594    -0.84   0.402     -.937943    .3762496
                               MO  |   .9713261    .322437     3.01   0.003     .3393612    1.603291
                               MT  |   .3610535   .2966765     1.22   0.224    -.2204219    .9425288
                               NE  |   .3883445   .3059471     1.27   0.204    -.2113007    .9879898
                               NV  |   .6952901   .3162482     2.20   0.028      .075455    1.315125
                               NH  |   .4168677   .3253808     1.28   0.200     -.220867    1.054602
                               NJ  |   1.164997   .3436079     3.39   0.001     .4915375    1.838456
                               NM  |   .8410327    .335891     2.50   0.012     .1826984    1.499367
                               NY  |   1.690309   .4939313     3.42   0.001     .7222218    2.658397
                               NC  |   .4035687   .2879264     1.40   0.161    -.1607567    .9678941
                               ND  |   .2017014   .2989622     0.67   0.500    -.3842538    .7876566
                               OH  |    .554993    .311593     1.78   0.075    -.0557182    1.165704
                               OK  |  -.2453247   .3034685    -0.81   0.419    -.8401121    .3494627
                               OR  |   .1486183   .3074393     0.48   0.629    -.4539517    .7511883
                               PA  |    .674903   .3150223     2.14   0.032     .0574706    1.292335
                               RI  |   .6151775   .3382438     1.82   0.069    -.0477681    1.278123
                               SC  |  -.5484811   .3254676    -1.69   0.092    -1.186386    .0894237
                               SD  |   .8152764   .3276369     2.49   0.013     .1731198    1.457433
                               TN  |   .5358593   .3149183     1.70   0.089    -.0813691    1.153088
                               TX  |   -.512813    .344921    -1.49   0.137    -1.188846    .1632197
                               UT  |   .2776748   .2921539     0.95   0.342    -.2949364    .8502859
                               VT  |   .6276337   .3259051     1.93   0.054    -.0111287    1.266396
                               VA  |   .7118361   .3366831     2.11   0.034     .0519493    1.371723
                               WA  |   .7932817   .3229908     2.46   0.014     .1602314    1.426332
                               WV  |   .4469914   .3266186     1.37   0.171    -.1931693    1.087152
                               WI  |   1.047169    .315109     3.32   0.001      .429567    1.664771
                               WY  |   .2113588   .2974966     0.71   0.477    -.3717238    .7944414
                                   |
                              year |
                             1984  |  -.1050642   .1187722    -0.88   0.376    -.3378536    .1277251
                             1988  |  -.1155315    .114267    -1.01   0.312    -.3394906    .1084277
                             1994  |   .1511807   .1204465     1.26   0.209    -.0848902    .3872516
                             1998  |   .2817377    .130739     2.15   0.031      .025494    .5379815
                             2004  |   .0353798   .1363843     0.26   0.795    -.2319286    .3026882
                             2008  |   .1458816   .1467646     0.99   0.320    -.1417717    .4335348
                                   |
                             _cons |  -1.905624   .8814126    -2.16   0.031    -3.633161   -.1780875
----------------------------------------------------------------------------------------------------

. 
. est sto mlogit5

. 
.  esttab mlogit5 using Table_B12.rtf  ,starlevels(+ 0.10 * 0.05 ** 0.01) cells(b(star fmt(3)) se(par fmt(3))
> ) ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Gov. Policy" ) 
(output written to Table_B12.rtf)

. 
. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B13 ******
.  mlogit d_16a i.intersection i.reve_1c  i.reve_1d i.civil_service weekly_hours age age_2 b3.edu years_emplo
> y_state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.f
> uncat13 i.state i.year , base(2) r 

Iteration 0:   log pseudolikelihood = -6643.7859  
Iteration 1:   log pseudolikelihood = -6534.7783  
Iteration 2:   log pseudolikelihood = -6347.6028  
Iteration 3:   log pseudolikelihood = -6310.4918  
Iteration 4:   log pseudolikelihood = -6276.9712  
Iteration 5:   log pseudolikelihood = -6275.4355  
Iteration 6:   log pseudolikelihood =  -6275.246  
Iteration 7:   log pseudolikelihood = -6275.2023  
Iteration 8:   log pseudolikelihood = -6275.1915  
Iteration 9:   log pseudolikelihood = -6275.1894  
Iteration 10:  log pseudolikelihood = -6275.1889  
Iteration 11:  log pseudolikelihood = -6275.1888  
Iteration 12:  log pseudolikelihood = -6275.1888  

Multinomial logistic regression                 Number of obs     =      6,200
                                                Wald chi2(300)    =    7926.82
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -6275.1888               Pseudo R2         =     0.0555

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_16a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
None                               |
                      intersection |
                      White Woman  |   .4353519   .2803751     1.55   0.120    -.1141732    .9848769
                     Man of Color  |   .4151341   .3721326     1.12   0.265    -.3142323    1.144501
                   Woman of Color  |   .3409834   .7854376     0.43   0.664    -1.198446    1.880413
                                   |
                           reve_1c |
                Less than Monthly  |  -.4028139   .5124517    -0.79   0.432    -1.407201     .601573
                          Monthly  |  -.7879798   .5653916    -1.39   0.163    -1.896127    .3201674
                           Weekly  |  -1.407478    .589425    -2.39   0.017     -2.56273   -.2522262
                            Daily  |  -.2545797   .7594117    -0.34   0.737    -1.742999     1.23384
                                   |
                           reve_1d |
                Less than Monthly  |  -1.822254   .3423333    -5.32   0.000    -2.493215   -1.151293
                          Monthly  |  -2.266683   .3953161    -5.73   0.000    -3.041488   -1.491878
                           Weekly  |  -2.394661   .4467468    -5.36   0.000    -3.270268   -1.519053
                            Daily  |  -2.056393   .6689898    -3.07   0.002    -3.367588   -.7451968
                                   |
                     civil_service |
                              Yes  |  -.2361249    .248652    -0.95   0.342    -.7234738     .251224
                      weekly_hours |  -.0103623   .0131284    -0.79   0.430    -.0360936     .015369
                               age |   .2727119   .1110693     2.46   0.014       .05502    .4904038
                             age_2 |  -.0024573   .0010795    -2.28   0.023    -.0045731   -.0003416
                                   |
                               edu |
              High school or less  |   .3025144   .8134463     0.37   0.710    -1.291811     1.89684
                     Some college  |   .3807274   .4123243     0.92   0.356    -.4274133    1.188868
                   Graduate study  |  -.2850739   .3462337    -0.82   0.410    -.9636796    .3935318
                  Graduate degree  |    -.11683   .2850566    -0.41   0.682    -.6755307    .4418706
                                   |
                years_employ_state |  -.0090221   .0171792    -0.53   0.599    -.0426927    .0246485
               years_employ_agency |  -.0148499   .0178523    -0.83   0.406    -.0498397      .02014
             years_employ_position |   .0399224    .019559     2.04   0.041     .0015874    .0782573
                                   |
                              pid5 |
                       Republican  |   .0597352   .3241876     0.18   0.854    -.5756608    .6951313
                  Lean Republican  |  -.3141032   .4669259    -0.67   0.501    -1.229261    .6010547
                  Lean Democratic  |  -.7818296   .5488465    -1.42   0.154    -1.857549    .2938897
                       Democratic  |  -.1817681   .2989286    -0.61   0.543    -.7676575    .4041213
                                   |
                       agency_size |
                           25-100  |  -.7667545     .28402    -2.70   0.007    -1.323423   -.2100855
                          101-500  |  -.5750452   .3314571    -1.73   0.083    -1.224689    .0745988
                        501-1,000  |  -.6968831   .5044915    -1.38   0.167    -1.685668    .2919021
                      1,001-5,000  |  -1.085621   .5921545    -1.83   0.067    -2.246222    .0749803
                       Over 5,000  |  -.4931577   .7277635    -0.68   0.498    -1.919548    .9332326
                                   |
                 log_agency_budget |   -.009714   .0881915    -0.11   0.912    -.1825661    .1631382
                      inst6017_nom |  -.0094848   .0131498    -0.72   0.471     -.035258    .0162884
                                   |
                          funcat13 |
                    Staff: Fiscal  |   .0126405   .6540814     0.02   0.985    -1.269335    1.294616
                Staff: Non-Fiscal  |  -.4540655   .6767391    -0.67   0.502     -1.78045    .8723188
Income Security & Social Services  |  -1.061549   .7207598    -1.47   0.141    -2.474212    .3511144
                        Education  |    -.21508   .7141248    -0.30   0.763    -1.614739    1.184579
                           Health  |   -1.52019   .9427078    -1.61   0.107    -3.367864    .3274829
                Natural Resources  |  -.6054926   .6104315    -0.99   0.321    -1.801916    .5909311
             Environment & Energy  |  -.2495315   .6377922    -0.39   0.696    -1.499581    1.000518
             Economic Development  |  -.2742776   .6384468    -0.43   0.667     -1.52561    .9770551
                 Criminal Justice  |  -.0961607    .663076    -0.15   0.885    -1.395766    1.203444
                       Regulatory  |  -.1131175   .5857461    -0.19   0.847    -1.261159    1.034924
                   Transportation  |  -.7424445   .6954372    -1.07   0.286    -2.105476    .6205875
                            Other  |   .4097955   .5644478     0.73   0.468    -.6965019    1.516093
                                   |
                             state |
                               AK  |  -.8482398   .7813571    -1.09   0.278    -2.379672     .683192
                               AZ  |  -.8079116    .690257    -1.17   0.242     -2.16079    .5449673
                               AR  |  -1.081283   .8994602    -1.20   0.229    -2.844192     .681627
                               CA  |  -1.528382   1.170385    -1.31   0.192    -3.822295    .7655317
                               CO  |  -.8657547    .751818    -1.15   0.250    -2.339291    .6077815
                               CT  |    -.94242   1.158093    -0.81   0.416    -3.212241    1.327401
                               DE  |  -2.186151   1.167964    -1.87   0.061    -4.475318    .1030153
                               FL  |  -.3088391    .780231    -0.40   0.692    -1.838064    1.220386
                               GA  |  -1.298871   1.151124    -1.13   0.259    -3.555033    .9572912
                               HI  |  -1.123259   .8011172    -1.40   0.161    -2.693419    .4469021
                               ID  |  -2.580932   1.179731    -2.19   0.029    -4.893162   -.2687024
                               IL  |  -1.530843   1.099466    -1.39   0.164    -3.685758    .6240719
                               IN  |  -1.886639   .9298013    -2.03   0.042    -3.709016    -.064262
                               IA  |  -1.364727    .855187    -1.60   0.111    -3.040862    .3114091
                               KS  |  -1.353053   .9235157    -1.47   0.143    -3.163111    .4570044
                               KY  |  -1.852107   1.133568    -1.63   0.102     -4.07386    .3696462
                               LA  |  -.1105219   .7222998    -0.15   0.878    -1.526203     1.30516
                               ME  |  -1.375534   1.143104    -1.20   0.229    -3.615977    .8649099
                               MD  |  -.8158457    .890626    -0.92   0.360     -2.56144    .9297491
                               MA  |  -1.452361   1.142039    -1.27   0.203    -3.690717     .785994
                               MI  |  -.2391178   .6882508    -0.35   0.728    -1.588065    1.109829
                               MN  |   -1.64867   1.096246    -1.50   0.133    -3.797273    .4999335
                               MS  |  -.9864703   .7670144    -1.29   0.198    -2.489791    .5168502
                               MO  |  -1.037848   .9074719    -1.14   0.253    -2.816461    .7407638
                               MT  |  -1.517535   .7371062    -2.06   0.040    -2.962236   -.0728329
                               NE  |  -1.076347   .7412253    -1.45   0.146    -2.529122    .3764279
                               NV  |  -1.658017   .8968987    -1.85   0.065    -3.415906     .099872
                               NH  |  -1.308725   .9592535    -1.36   0.172    -3.188827    .5713776
                               NJ  |  -14.70272   .5360177   -27.43   0.000     -15.7533   -13.65215
                               NM  |  -.8549604   .6818388    -1.25   0.210     -2.19134     .481419
                               NY  |  -1.539871   1.076957    -1.43   0.153    -3.650668    .5709262
                               NC  |  -.2536072   .6063484    -0.42   0.676    -1.442028    .9348138
                               ND  |  -1.873494   .9061199    -2.07   0.039    -3.649456   -.0975316
                               OH  |  -.4845935   .6730812    -0.72   0.472    -1.803808    .8346215
                               OK  |  -1.186348   .9484035    -1.25   0.211    -3.045185    .6724885
                               OR  |  -15.04342   .5163324   -29.14   0.000    -16.05542   -14.03143
                               PA  |  -.6093758   .6765213    -0.90   0.368    -1.935333    .7165815
                               RI  |  -1.874183   1.075185    -1.74   0.081    -3.981506    .2331408
                               SC  |   .2566557   .6455337     0.40   0.691    -1.008567    1.521878
                               SD  |   -2.16492   .8884511    -2.44   0.015    -3.906252   -.4235879
                               TN  |   -1.62929   1.150985    -1.42   0.157     -3.88518    .6265994
                               TX  |  -1.826877   .8484394    -2.15   0.031    -3.489787    -.163966
                               UT  |  -2.416506    1.10304    -2.19   0.028    -4.578426   -.2545867
                               VT  |  -1.585224   .8768436    -1.81   0.071    -3.303806    .1333575
                               VA  |  -1.617965   1.144154    -1.41   0.157    -3.860466     .624536
                               WA  |  -1.664276   1.171335    -1.42   0.155    -3.960051    .6314986
                               WV  |  -.1357594   .6720633    -0.20   0.840    -1.452979    1.181461
                               WI  |  -1.746844   1.109944    -1.57   0.116    -3.922295    .4286075
                               WY  |  -.6793042   .5862776    -1.16   0.247    -1.828387    .4697787
                                   |
                              year |
                             1984  |  -.3362877   .3303259    -1.02   0.309    -.9837147    .3111392
                             1988  |   -.304571   .3085378    -0.99   0.324     -.909294     .300152
                             1994  |  -.3109993   .3449579    -0.90   0.367    -.9871043    .3651057
                             1998  |  -.9201298   .3774946    -2.44   0.015    -1.660006    -.180254
                             2004  |  -1.236081   .4565783    -2.71   0.007    -2.130958   -.3412035
                             2008  |  -.9540187   .4414351    -2.16   0.031    -1.819216   -.0888219
                                   |
                             _cons |  -3.927482   3.024766    -1.30   0.194    -9.855914     2.00095
-----------------------------------+----------------------------------------------------------------
Slight                             |
                      intersection |
                      White Woman  |  -.2907699   .1276655    -2.28   0.023    -.5409896   -.0405502
                     Man of Color  |   .3169126   .1663756     1.90   0.057    -.0091776    .6430029
                   Woman of Color  |    .194247   .3135288     0.62   0.536    -.4202582    .8087522
                                   |
                           reve_1c |
                Less than Monthly  |   .1361297   .4290754     0.32   0.751    -.7048426     .977102
                          Monthly  |   .0301693   .4328633     0.07   0.944    -.8182271    .8785657
                           Weekly  |  -.0940668   .4378389    -0.21   0.830    -.9522153    .7640817
                            Daily  |  -.0022331   .4741238    -0.00   0.996    -.9314987    .9270324
                                   |
                           reve_1d |
                Less than Monthly  |  -.2240828   .2676219    -0.84   0.402     -.748612    .3004464
                          Monthly  |  -.4418704   .2731026    -1.62   0.106    -.9771417    .0934009
                           Weekly  |  -.4791671   .2803222    -1.71   0.087    -1.028588    .0702542
                            Daily  |  -.8295865   .3536737    -2.35   0.019    -1.522774   -.1363987
                                   |
                     civil_service |
                              Yes  |  -.1108137   .1076399    -1.03   0.303    -.3217841    .1001566
                      weekly_hours |      .0054   .0054295     0.99   0.320    -.0052416    .0160415
                               age |  -.0337952   .0369477    -0.91   0.360    -.1062113     .038621
                             age_2 |   .0003785   .0003643     1.04   0.299    -.0003356    .0010925
                                   |
                               edu |
              High school or less  |   .5305011   .3772178     1.41   0.160    -.2088322    1.269834
                     Some college  |  -.0193467   .2011755    -0.10   0.923    -.4136435    .3749501
                   Graduate study  |  -.1833439   .1468639    -1.25   0.212    -.4711918     .104504
                  Graduate degree  |  -.0553507   .1144572    -0.48   0.629    -.2796826    .1689812
                                   |
                years_employ_state |  -.0092193   .0078392    -1.18   0.240    -.0245838    .0061452
               years_employ_agency |   .0130631   .0082353     1.59   0.113    -.0030778    .0292039
             years_employ_position |   .0100129   .0094011     1.07   0.287     -.008413    .0284388
                                   |
                              pid5 |
                       Republican  |  -.0627093   .1412755    -0.44   0.657    -.3396042    .2141855
                  Lean Republican  |   .0420744   .1872167     0.22   0.822    -.3248635    .4090123
                  Lean Democratic  |   .0255423   .1837987     0.14   0.889    -.3346965    .3857811
                       Democratic  |   .1355368   .1353266     1.00   0.317    -.1296985     .400772
                                   |
                       agency_size |
                           25-100  |  -.0833814   .1287656    -0.65   0.517    -.3357573    .1689946
                          101-500  |  -.2088291   .1511746    -1.38   0.167    -.5051259    .0874676
                        501-1,000  |   .1605247   .1985426     0.81   0.419    -.2286116     .549661
                      1,001-5,000  |   .1217224   .2078736     0.59   0.558    -.2857024    .5291473
                       Over 5,000  |   .1925051   .2833847     0.68   0.497    -.3629187    .7479288
                                   |
                 log_agency_budget |  -.0519825   .0355358    -1.46   0.144    -.1216314    .0176664
                      inst6017_nom |  -.0123463   .0052651    -2.34   0.019    -.0226658   -.0020269
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.5359914   .2703665    -1.98   0.047      -1.0659   -.0060828
                Staff: Non-Fiscal  |  -.5112726   .2758526    -1.85   0.064    -1.051934    .0293886
Income Security & Social Services  |   -.296974   .2467382    -1.20   0.229    -.7805721     .186624
                        Education  |  -.6186203   .2891354    -2.14   0.032    -1.185315   -.0519254
                           Health  |  -.4689646   .2691481    -1.74   0.081    -.9964851    .0585559
                Natural Resources  |   -.555647   .2301899    -2.41   0.016    -1.006811    -.104483
             Environment & Energy  |  -.7503589   .2518097    -2.98   0.003    -1.243897    -.256821
             Economic Development  |  -.3545218   .2430099    -1.46   0.145    -.8308123    .1217688
                 Criminal Justice  |  -.7409463   .2536617    -2.92   0.003    -1.238114   -.2437786
                       Regulatory  |  -.4922212   .2336206    -2.11   0.035    -.9501091   -.0343333
                   Transportation  |   -.887993   .2819402    -3.15   0.002    -1.440586   -.3354003
                            Other  |  -.4092924   .2382525    -1.72   0.086    -.8762586    .0576739
                                   |
                             state |
                               AK  |   -.859323   .4035399    -2.13   0.033    -1.650247   -.0683993
                               AZ  |  -.4839891   .3791333    -1.28   0.202    -1.227077    .2590985
                               AR  |  -.7314252   .3922649    -1.86   0.062     -1.50025       .0374
                               CA  |  -.2911305    .409411    -0.71   0.477    -1.093561    .5113003
                               CO  |  -.6319565   .3772437    -1.68   0.094    -1.371341    .1074275
                               CT  |   -.726655   .5145886    -1.41   0.158     -1.73523    .2819201
                               DE  |  -.6124475   .3893807    -1.57   0.116     -1.37562    .1507246
                               FL  |  -.9755022   .4663927    -2.09   0.036    -1.889615   -.0613893
                               GA  |    .249525    .349531     0.71   0.475    -.4355431    .9345932
                               HI  |    -.63536   .3980447    -1.60   0.110    -1.415513    .1447934
                               ID  |  -.4106746   .3503704    -1.17   0.241    -1.097388    .2760388
                               IL  |  -.3264848   .3910553    -0.83   0.404    -1.092939    .4399695
                               IN  |  -.5995026   .3634572    -1.65   0.099    -1.311866    .1128604
                               IA  |  -.5435074   .3570089    -1.52   0.128    -1.243232    .1562171
                               KS  |  -.4226053   .3842587    -1.10   0.271    -1.175739     .330528
                               KY  |  -.5983821   .3843719    -1.56   0.120    -1.351737     .154973
                               LA  |  -.1767769   .3733855    -0.47   0.636     -.908599    .5550452
                               ME  |    -.53069    .437929    -1.21   0.226    -1.389015    .3276351
                               MD  |  -.0640235    .360511    -0.18   0.859     -.770612    .6425651
                               MA  |   -.207336   .3824943    -0.54   0.588    -.9570111    .5423391
                               MI  |  -.1379524   .3551822    -0.39   0.698    -.8340967    .5581919
                               MN  |  -.9527383   .4376436    -2.18   0.029    -1.810504   -.0949727
                               MS  |  -.5556963   .3873628    -1.43   0.151    -1.314913    .2035208
                               MO  |   .0645756   .3438132     0.19   0.851    -.6092858     .738437
                               MT  |  -.7864883   .3545236    -2.22   0.027    -1.481342   -.0916347
                               NE  |  -.6605891   .3832222    -1.72   0.085    -1.411691    .0905127
                               NV  |  -.9539673   .4044764    -2.36   0.018    -1.746726   -.1612081
                               NH  |  -1.403047    .485533    -2.89   0.004    -2.354675   -.4514202
                               NJ  |  -.4688747   .3841338    -1.22   0.222    -1.221763    .2840138
                               NM  |  -.6777159   .4033496    -1.68   0.093    -1.468267    .1128349
                               NY  |  -.7730682   .4854247    -1.59   0.111    -1.724483    .1783467
                               NC  |  -.7332213   .3549576    -2.07   0.039    -1.428925   -.0375172
                               ND  |  -.8290961   .3597726    -2.30   0.021    -1.534237   -.1239548
                               OH  |  -.1072285    .348227    -0.31   0.758    -.7897408    .5752839
                               OK  |  -.3176098   .3914192    -0.81   0.417    -1.084777    .4495577
                               OR  |  -1.544059   .5328972    -2.90   0.004    -2.588518   -.4995994
                               PA  |  -.3201924   .3424064    -0.94   0.350    -.9912965    .3509118
                               RI  |  -.1514592   .3800492    -0.40   0.690     -.896342    .5934236
                               SC  |  -.4871059   .4067389    -1.20   0.231    -1.284299    .3100878
                               SD  |  -.3452166    .334751    -1.03   0.302    -1.001316    .3108832
                               TN  |    .035607    .346355     0.10   0.918    -.6432362    .7144502
                               TX  |  -.6043338   .4381956    -1.38   0.168    -1.463181    .2545137
                               UT  |  -.3742024   .3505229    -1.07   0.286    -1.061215    .3128098
                               VT  |  -.7152757   .3914279    -1.83   0.068     -1.48246    .0519089
                               VA  |  -.7546416   .4209476    -1.79   0.073    -1.579684    .0704006
                               WA  |  -.0746071   .3756425    -0.20   0.843    -.8108529    .6616387
                               WV  |  -.4825324    .377975    -1.28   0.202     -1.22335    .2582849
                               WI  |  -.5240315   .3704094    -1.41   0.157    -1.250021    .2019576
                               WY  |  -.6666313   .3533107    -1.89   0.059    -1.359108    .0258449
                                   |
                              year |
                             1984  |  -.2030264   .1540577    -1.32   0.188     -.504974    .0989212
                             1988  |  -.2182041   .1426713    -1.53   0.126    -.4978347    .0614265
                             1994  |  -.1079878   .1548052    -0.70   0.485    -.4114004    .1954248
                             1998  |  -.3825057   .1707956    -2.24   0.025     -.717259   -.0477524
                             2004  |  -.1408832   .1672904    -0.84   0.400    -.4687664        .187
                             2008  |  -.1637778   .1875141    -0.87   0.382    -.5312986     .203743
                                   |
                             _cons |   1.800537   1.097427     1.64   0.101    -.3503811    3.951454
-----------------------------------+----------------------------------------------------------------
Moderate                           |  (base outcome)
-----------------------------------+----------------------------------------------------------------
High                               |
                      intersection |
                      White Woman  |  -.0458822   .0843869    -0.54   0.587    -.2112774     .119513
                     Man of Color  |   .4611011   .1215425     3.79   0.000     .2228822      .69932
                   Woman of Color  |   .5670033   .2221766     2.55   0.011     .1315451    1.002462
                                   |
                           reve_1c |
                Less than Monthly  |  -.5416424    .270463    -2.00   0.045     -1.07174   -.0115446
                          Monthly  |  -.5820615   .2730737    -2.13   0.033    -1.117276    -.046847
                           Weekly  |  -.5101193   .2793229    -1.83   0.068    -1.057582    .0373435
                            Daily  |  -.4671056    .301671    -1.55   0.122     -1.05837    .1241586
                                   |
                           reve_1d |
                Less than Monthly  |   .0185479   .2245712     0.08   0.934    -.4216036    .4586994
                          Monthly  |   .0853897   .2258663     0.38   0.705       -.3573    .5280795
                           Weekly  |   .2751131   .2308788     1.19   0.233    -.1774011    .7276272
                            Daily  |   .5818451   .2582992     2.25   0.024     .0755879    1.088102
                                   |
                     civil_service |
                              Yes  |   .0074755   .0740116     0.10   0.920    -.1375845    .1525355
                      weekly_hours |  -.0008634    .003673    -0.24   0.814    -.0080623    .0063356
                               age |     .05499   .0297463     1.85   0.065    -.0033117    .1132916
                             age_2 |  -.0004548   .0002968    -1.53   0.125    -.0010365    .0001269
                                   |
                               edu |
              High school or less  |   .3299366   .3005434     1.10   0.272    -.2591176    .9189908
                     Some college  |  -.1212527    .143039    -0.85   0.397    -.4016039    .1590986
                   Graduate study  |  -.0294261   .1000487    -0.29   0.769    -.2255178    .1666657
                  Graduate degree  |  -.1073577   .0812767    -1.32   0.187    -.2666571    .0519416
                                   |
                years_employ_state |   .0042157   .0050015     0.84   0.399     -.005587    .0140184
               years_employ_agency |  -.0058872   .0052612    -1.12   0.263    -.0161991    .0044246
             years_employ_position |  -.0021212   .0072052    -0.29   0.768    -.0162433    .0120008
                                   |
                              pid5 |
                       Republican  |  -.1980986   .1017441    -1.95   0.052    -.3975134    .0013163
                  Lean Republican  |   .0181731   .1322607     0.14   0.891     -.241053    .2773993
                  Lean Democratic  |  -.0049265   .1268068    -0.04   0.969    -.2534632    .2436103
                       Democratic  |  -.0461865   .0946514    -0.49   0.626    -.2316999    .1393269
                                   |
                       agency_size |
                           25-100  |  -.0076923   .0922626    -0.08   0.934    -.1885237    .1731391
                          101-500  |   -.043773   .1056835    -0.41   0.679    -.2509088    .1633628
                        501-1,000  |  -.0933454   .1416536    -0.66   0.510    -.3709813    .1842905
                      1,001-5,000  |  -.2198198   .1470725    -1.49   0.135    -.5080766    .0684371
                       Over 5,000  |  -.1423762   .1991906    -0.71   0.475    -.5327825    .2480302
                                   |
                 log_agency_budget |   .0206787   .0244517     0.85   0.398    -.0272457    .0686031
                      inst6017_nom |   .0020935   .0037035     0.57   0.572    -.0051652    .0093523
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.3219325   .1897436    -1.70   0.090    -.6938231    .0499582
                Staff: Non-Fiscal  |  -.2624329   .1941442    -1.35   0.176    -.6429485    .1180826
Income Security & Social Services  |  -.3992861   .1805769    -2.21   0.027    -.7532103   -.0453619
                        Education  |  -.1985247   .1995613    -0.99   0.320    -.5896576    .1926083
                           Health  |  -.2857391    .192966    -1.48   0.139    -.6639455    .0924674
                Natural Resources  |  -.6002348   .1717227    -3.50   0.000    -.9368051   -.2636645
             Environment & Energy  |  -.2450611   .1773604    -1.38   0.167    -.5926812     .102559
             Economic Development  |  -.5917564   .1832594    -3.23   0.001    -.9509382   -.2325746
                 Criminal Justice  |  -.1062926   .1810659    -0.59   0.557    -.4611753    .2485901
                       Regulatory  |  -.1948775   .1693032    -1.15   0.250    -.5267056    .1369505
                   Transportation  |  -.3792122   .1929325    -1.97   0.049     -.757353   -.0010714
                            Other  |  -.6517646   .1809698    -3.60   0.000    -1.006459   -.2970703
                                   |
                             state |
                               AK  |    .313438   .2918483     1.07   0.283    -.2585741    .8854501
                               AZ  |    .567065   .3065666     1.85   0.064    -.0337946    1.167925
                               AR  |   .1643685   .3046103     0.54   0.589    -.4326567    .7613937
                               CA  |   .5400191   .3138379     1.72   0.085    -.0750918     1.15513
                               CO  |    .713927   .2992713     2.39   0.017      .127366    1.300488
                               CT  |   .4583882   .3456826     1.33   0.185    -.2191372    1.135914
                               DE  |   .4755616   .2972825     1.60   0.110    -.1071013    1.058225
                               FL  |   .7610523   .3072523     2.48   0.013     .1588489    1.363256
                               GA  |   .5700265   .3141811     1.81   0.070     -.045757     1.18581
                               HI  |   .1139011   .3163282     0.36   0.719    -.5060909     .733893
                               ID  |   .3848234   .2998412     1.28   0.199    -.2028547    .9725014
                               IL  |   .0526885   .3315432     0.16   0.874    -.5971242    .7025012
                               IN  |   .1061561   .3070326     0.35   0.730    -.4956168     .707929
                               IA  |   .5926747   .2879881     2.06   0.040     .0282283    1.157121
                               KS  |   .9395827   .2993287     3.14   0.002     .3529093    1.526256
                               KY  |   .0721415   .3043476     0.24   0.813    -.5243689    .6686519
                               LA  |  -.0466712   .3235489    -0.14   0.885    -.6808154    .5874729
                               ME  |   .8466522   .3154289     2.68   0.007      .228423    1.464882
                               MD  |   .3452373   .3005413     1.15   0.251    -.2438128    .9342874
                               MA  |  -.4977787   .3469118    -1.43   0.151    -1.177713    .1821558
                               MI  |  -.0303917   .3016376    -0.10   0.920    -.6215905    .5608071
                               MN  |   .7760611   .2884218     2.69   0.007     .2107647    1.341357
                               MS  |   .6362477   .3005638     2.12   0.034     .0471535    1.225342
                               MO  |   .3978649   .2958603     1.34   0.179    -.1820106    .9777403
                               MT  |    .249156   .2827643     0.88   0.378    -.3050517    .8033638
                               NE  |   .6653979   .2984346     2.23   0.026     .0804768    1.250319
                               NV  |   .4955568    .293762     1.69   0.092    -.0802061     1.07132
                               NH  |   .7288649   .3086107     2.36   0.018     .1239991    1.333731
                               NJ  |   .3385501   .3087947     1.10   0.273    -.2666764    .9437766
                               NM  |   .3809726   .3095313     1.23   0.218    -.2256976    .9876427
                               NY  |   .0790105   .3573539     0.22   0.825    -.6213902    .7794113
                               NC  |   .5061858   .2787544     1.82   0.069    -.0401628    1.052534
                               ND  |    .361616   .2923599     1.24   0.216    -.2113989    .9346309
                               OH  |   .3148993   .3013361     1.05   0.296    -.2757087    .9055073
                               OK  |   1.018386   .2993003     3.40   0.001     .4317679    1.605004
                               OR  |   .7532001   .2958573     2.55   0.011     .1733303     1.33307
                               PA  |  -.2424575   .3128636    -0.77   0.438     -.855659    .3707439
                               RI  |   .1698864   .3277788     0.52   0.604    -.4725482     .812321
                               SC  |   .6029468   .3112182     1.94   0.053    -.0070297    1.212923
                               SD  |   .0385739   .3072068     0.13   0.900    -.5635403    .6406881
                               TN  |   .0433263   .3159354     0.14   0.891    -.5758957    .6625483
                               TX  |   .9287969   .3166913     2.93   0.003     .3080934      1.5495
                               UT  |   .8471069   .2893852     2.93   0.003     .2799224    1.414291
                               VT  |   .2691282   .3001679     0.90   0.370    -.3191902    .8574465
                               VA  |   .5675423   .3159558     1.80   0.072    -.0517196    1.186804
                               WA  |   .6846624   .3019884     2.27   0.023     .0927759    1.276549
                               WV  |   .3730028   .3037106     1.23   0.219    -.2222591    .9682647
                               WI  |   .3534022   .2932791     1.21   0.228    -.2214143    .9282188
                               WY  |   .4252936   .2898334     1.47   0.142    -.1427695    .9933567
                                   |
                              year |
                             1984  |  -.0827013    .109531    -0.76   0.450    -.2973782    .1319756
                             1988  |  -.1315251   .1041975    -1.26   0.207    -.3357484    .0726982
                             1994  |   .1154111   .1114172     1.04   0.300    -.1029626    .3337847
                             1998  |   .1303665   .1180158     1.10   0.269    -.1009402    .3616732
                             2004  |  -.0744006   .1241445    -0.60   0.549    -.3177194    .1689181
                             2008  |   .0834546   .1332405     0.63   0.531    -.1776919    .3446011
                                   |
                             _cons |  -.9872808    .844222    -1.17   0.242    -2.641926     .667364
----------------------------------------------------------------------------------------------------

. 
. est sto mlogit6

. 
.  esttab mlogit6 using Table_B13.rtf  ,starlevels(+ 0.10 * 0.05 ** 0.01) cells(b(star fmt(3)) se(par fmt(3))
> ) ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Legis. Policy" ) 
(output written to Table_B13.rtf)

. 
. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B14 ******
. mlogit d_20a i.intersection i.reve_1a i.reve_1b  i.civil_service weekly_hours age age_2 b3.edu years_employ
> _state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fu
> ncat13 i.state i.year , base(2) r  

Iteration 0:   log pseudolikelihood = -7996.7677  
Iteration 1:   log pseudolikelihood = -7392.9569  
Iteration 2:   log pseudolikelihood =    -7281.8  
Iteration 3:   log pseudolikelihood = -7274.8999  
Iteration 4:   log pseudolikelihood = -7274.8709  
Iteration 5:   log pseudolikelihood = -7274.8709  

Multinomial logistic regression                 Number of obs     =      6,175
                                                Wald chi2(300)    =    1277.08
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -7274.8709               Pseudo R2         =     0.0903

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_20a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
None                               |
                      intersection |
                      White Woman  |    .394664   .1574531     2.51   0.012     .0860615    .7032665
                     Man of Color  |   .1065129   .2194825     0.49   0.627    -.3236649    .5366907
                   Woman of Color  |   .2194685   .4369488     0.50   0.615    -.6369353    1.075872
                                   |
                           reve_1a |
                Less than Monthly  |  -.5211777   .1516304    -3.44   0.001    -.8183677   -.2239876
                          Monthly  |  -.4936781   .2151803    -2.29   0.022    -.9154237   -.0719324
                           Weekly  |   -.768377   .2866878    -2.68   0.007    -1.330275   -.2064792
                            Daily  |  -.3927431   .5607644    -0.70   0.484    -1.491821    .7063349
                                   |
                           reve_1b |
                Less than Monthly  |  -.6601384   .2828121    -2.33   0.020     -1.21444   -.1058367
                          Monthly  |  -1.078812   .3052626    -3.53   0.000    -1.677116   -.4805083
                           Weekly  |  -1.308503   .3202134    -4.09   0.000     -1.93611   -.6808963
                            Daily  |  -1.825403   .3780952    -4.83   0.000    -2.566456    -1.08435
                                   |
                     civil_service |
                              Yes  |   -.399145   .1418902    -2.81   0.005    -.6772448   -.1210453
                      weekly_hours |  -.0010587   .0069763    -0.15   0.879    -.0147319    .0126146
                               age |    .093239   .0571557     1.63   0.103    -.0187841    .2052621
                             age_2 |  -.0007692   .0005638    -1.36   0.172    -.0018742    .0003358
                                   |
                               edu |
              High school or less  |   -.483484   .5438611    -0.89   0.374    -1.549432    .5824641
                     Some college  |  -.2621977   .2748506    -0.95   0.340    -.8008951    .2764996
                   Graduate study  |  -.2691681   .1862811    -1.44   0.148    -.6342723    .0959362
                  Graduate degree  |   .0575094   .1443417     0.40   0.690     -.225395    .3404139
                                   |
                years_employ_state |   .0048413   .0094308     0.51   0.608    -.0136426    .0233252
               years_employ_agency |  -.0017742    .009846    -0.18   0.857    -.0210721    .0175237
             years_employ_position |   .0464234   .0114293     4.06   0.000     .0240224    .0688244
                                   |
                              pid5 |
                       Republican  |   .0942186   .1889123     0.50   0.618    -.2760427      .46448
                  Lean Republican  |   .3042706   .2383214     1.28   0.202    -.1628307     .771372
                  Lean Democratic  |   -.159749   .2554406    -0.63   0.532    -.6604032    .3409053
                       Democratic  |    .238308   .1707635     1.40   0.163    -.0963823    .5729983
                                   |
                       agency_size |
                           25-100  |  -.0102226   .1584861    -0.06   0.949    -.3208497    .3004044
                          101-500  |   .0165886    .184626     0.09   0.928    -.3452718    .3784489
                        501-1,000  |  -.1715963   .2683497    -0.64   0.523    -.6975521    .3543595
                      1,001-5,000  |   .2605541   .2742255     0.95   0.342     -.276918    .7980262
                       Over 5,000  |   .0646349   .4187231     0.15   0.877    -.7560472     .885317
                                   |
                 log_agency_budget |  -.1342219   .0460873    -2.91   0.004    -.2245513   -.0438925
                      inst6017_nom |  -.0104561   .0071005    -1.47   0.141    -.0243728    .0034606
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -2.321314    .344787    -6.73   0.000    -2.997084   -1.645544
                Staff: Non-Fiscal  |  -3.037536   .3829206    -7.93   0.000    -3.788047   -2.287026
Income Security & Social Services  |   -2.76746   .3086216    -8.97   0.000    -3.372347   -2.162573
                        Education  |    -2.0863   .3140122    -6.64   0.000    -2.701752   -1.470847
                           Health  |  -2.553837   .3580763    -7.13   0.000    -3.255654    -1.85202
                Natural Resources  |  -2.581125   .2700869    -9.56   0.000    -3.110486   -2.051764
             Environment & Energy  |  -2.531186   .2794929    -9.06   0.000    -3.078982    -1.98339
             Economic Development  |  -1.906732   .2898162    -6.58   0.000    -2.474761   -1.338702
                 Criminal Justice  |  -2.019471   .2812809    -7.18   0.000    -2.570772   -1.468171
                       Regulatory  |  -1.689189   .2396278    -7.05   0.000    -2.158851   -1.219527
                   Transportation  |   -2.40579   .3283398    -7.33   0.000    -3.049324   -1.762256
                            Other  |  -1.810735   .2738224    -6.61   0.000    -2.347417   -1.274053
                                   |
                             state |
                               AK  |  -1.429189   .5825869    -2.45   0.014    -2.571038   -.2873396
                               AZ  |  -.8385898   .4994186    -1.68   0.093    -1.817432    .1402526
                               AR  |  -.7923424   .5119258    -1.55   0.122    -1.795698    .2110137
                               CA  |  -.7858424   .5412609    -1.45   0.147    -1.846694    .2750096
                               CO  |   .1115091   .4364896     0.26   0.798    -.7439948     .967013
                               CT  |  -.6901732    .574845    -1.20   0.230    -1.816849    .4365022
                               DE  |  -1.788123   .6007009    -2.98   0.003    -2.965475   -.6107706
                               FL  |  -1.098956   .4974387    -2.21   0.027    -2.073918   -.1239937
                               GA  |  -1.324824   .5484309    -2.42   0.016    -2.399729   -.2499194
                               HI  |  -1.736866   .5810579    -2.99   0.003    -2.875719   -.5980139
                               ID  |  -.8921907   .5073164    -1.76   0.079    -1.886513    .1021312
                               IL  |  -.9157418   .5350358    -1.71   0.087    -1.964393    .1329092
                               IN  |  -1.556864   .5454403    -2.85   0.004    -2.625907   -.4878206
                               IA  |   -2.10542   .5837132    -3.61   0.000    -3.249477   -.9613629
                               KS  |   -.765949   .5253117    -1.46   0.145    -1.795541    .2636429
                               KY  |  -1.628717   .6267678    -2.60   0.009    -2.857159   -.4002744
                               LA  |  -1.003071   .5906374    -1.70   0.089    -2.160699    .1545566
                               ME  |  -.4984734   .5031188    -0.99   0.322    -1.484568    .4876214
                               MD  |  -.5718758   .4924335    -1.16   0.246    -1.537028    .3932761
                               MA  |  -.9551386   .5904029    -1.62   0.106    -2.112307    .2020298
                               MI  |  -1.441694   .5644386    -2.55   0.011    -2.547973   -.3354146
                               MN  |  -.4498312   .4599291    -0.98   0.328    -1.351276    .4516132
                               MS  |   .6457767   .4697732     1.37   0.169    -.2749618    1.566515
                               MO  |  -.8462936   .4746105    -1.78   0.075    -1.776513    .0839259
                               MT  |   -.767376   .4672081    -1.64   0.100    -1.683087    .1483349
                               NE  |   -1.81578   .5230727    -3.47   0.001    -2.840984   -.7905767
                               NV  |  -1.121651   .5215153    -2.15   0.031    -2.143802   -.0994999
                               NH  |  -1.084021   .5177465    -2.09   0.036    -2.098785   -.0692565
                               NJ  |  -1.986833   .6262591    -3.17   0.002    -3.214278   -.7593873
                               NM  |  -.6730483   .5161564    -1.30   0.192    -1.684696    .3385996
                               NY  |  -1.335176   .6248999    -2.14   0.033    -2.559957   -.1103947
                               NC  |  -.8370907   .4246773    -1.97   0.049    -1.669443   -.0047386
                               ND  |   -.927515   .4893941    -1.90   0.058     -1.88671    .0316799
                               OH  |  -1.596196   .5719163    -2.79   0.005    -2.717132   -.4752608
                               OK  |  -1.163203   .4996977    -2.33   0.020    -2.142593   -.1838138
                               OR  |  -1.054403    .506968    -2.08   0.038    -2.048042   -.0607641
                               PA  |  -1.727539    .544256    -3.17   0.002    -2.794261   -.6608163
                               RI  |  -.9641306   .5611874    -1.72   0.086    -2.064038    .1357765
                               SC  |  -1.083755     .50097    -2.16   0.031    -2.065638   -.1018718
                               SD  |  -1.296147   .5001403    -2.59   0.010    -2.276404   -.3158904
                               TN  |  -1.271746   .5458212    -2.33   0.020    -2.341536   -.2019562
                               TX  |  -.3101272   .4897621    -0.63   0.527    -1.270043    .6497888
                               UT  |  -2.240676   .5694121    -3.94   0.000    -3.356703   -1.124649
                               VT  |  -1.640538   .5607823    -2.93   0.003    -2.739651   -.5414251
                               VA  |  -1.510618   .6041014    -2.50   0.012    -2.694634   -.3266006
                               WA  |  -.8696419   .5034704    -1.73   0.084    -1.856426     .117142
                               WV  |  -1.083523   .5321569    -2.04   0.042    -2.126531   -.0405144
                               WI  |  -2.528881   .6234042    -4.06   0.000    -3.750731   -1.307031
                               WY  |  -1.028448    .521691    -1.97   0.049    -2.050944   -.0059525
                                   |
                              year |
                             1984  |  -.6325632   .1907397    -3.32   0.001    -1.006406   -.2587202
                             1988  |  -.7469455   .1816263    -4.11   0.000    -1.102927   -.3909645
                             1994  |   -1.29865   .2050349    -6.33   0.000    -1.700511   -.8967887
                             1998  |  -1.422182   .2182731    -6.52   0.000     -1.84999    -.994375
                             2004  |  -1.186768   .2224346    -5.34   0.000    -1.622732    -.750804
                             2008  |  -1.824109   .2566949    -7.11   0.000    -2.327222   -1.320996
                                   |
                             _cons |   2.093002   1.515851     1.38   0.167    -.8780107    5.064016
-----------------------------------+----------------------------------------------------------------
Slight                             |
                      intersection |
                      White Woman  |   .1267158   .0948139     1.34   0.181     -.059116    .3125475
                     Man of Color  |  -.3132872   .1419784    -2.21   0.027    -.5915597   -.0350147
                   Woman of Color  |   .0274518    .267303     0.10   0.918    -.4964526    .5513561
                                   |
                           reve_1a |
                Less than Monthly  |   .0469387    .102059     0.46   0.646    -.1530933    .2469708
                          Monthly  |  -.0556283    .129518    -0.43   0.668    -.3094788    .1982223
                           Weekly  |      .0631   .1627549     0.39   0.698    -.2558937    .3820937
                            Daily  |  -.2435757   .3397346    -0.72   0.473    -.9094433    .4222919
                                   |
                           reve_1b |
                Less than Monthly  |  -.2573786   .2497192    -1.03   0.303    -.7468193    .2320621
                          Monthly  |   -.333541   .2576455    -1.29   0.195     -.838517    .1714349
                           Weekly  |  -.5137868   .2620704    -1.96   0.050    -1.027435   -.0001383
                            Daily  |  -.8387542    .281234    -2.98   0.003    -1.389963   -.2875457
                                   |
                     civil_service |
                              Yes  |  -.0987604   .0867531    -1.14   0.255    -.2687933    .0712724
                      weekly_hours |   .0015353   .0043156     0.36   0.722    -.0069232    .0099938
                               age |   .0331615   .0339206     0.98   0.328    -.0333217    .0996448
                             age_2 |  -.0002881   .0003371    -0.85   0.393    -.0009488    .0003725
                                   |
                               edu |
              High school or less  |  -.0722669   .3426096    -0.21   0.833    -.7437693    .5992355
                     Some college  |   .1925051   .1694133     1.14   0.256    -.1395388     .524549
                   Graduate study  |  -.0227905   .1195334    -0.19   0.849    -.2570717    .2114906
                  Graduate degree  |   .2689645   .0961551     2.80   0.005     .0805039    .4574251
                                   |
                years_employ_state |   .0032467   .0056904     0.57   0.568    -.0079062    .0143996
               years_employ_agency |  -.0019828   .0060592    -0.33   0.743    -.0138586     .009893
             years_employ_position |   .0243418   .0081797     2.98   0.003     .0083099    .0403737
                                   |
                              pid5 |
                       Republican  |    .153088   .1166256     1.31   0.189     -.075494    .3816701
                  Lean Republican  |   .0298372    .152511     0.20   0.845     -.269079    .3287533
                  Lean Democratic  |   .0009888   .1407288     0.01   0.994    -.2748346    .2768122
                       Democratic  |    .065145   .1080807     0.60   0.547    -.1466892    .2769792
                                   |
                       agency_size |
                           25-100  |  -.0203651   .1103604    -0.18   0.854    -.2366675    .1959374
                          101-500  |  -.0350675    .124365    -0.28   0.778    -.2788183    .2086834
                        501-1,000  |   .0898035   .1592599     0.56   0.573    -.2223402    .4019472
                      1,001-5,000  |   -.025675   .1707128    -0.15   0.880     -.360266    .3089159
                       Over 5,000  |   .0714393   .2301841     0.31   0.756    -.3797133    .5225919
                                   |
                 log_agency_budget |  -.0096735   .0285805    -0.34   0.735    -.0656901    .0463432
                      inst6017_nom |  -.0025813   .0042097    -0.61   0.540    -.0108322    .0056695
                                   |
                          funcat13 |
                    Staff: Fiscal  |   -.898683   .2377283    -3.78   0.000    -1.364622    -.432744
                Staff: Non-Fiscal  |  -1.237915   .2514008    -4.92   0.000    -1.730652   -.7451786
Income Security & Social Services  |  -.8925212   .2195702    -4.06   0.000    -1.322871   -.4621715
                        Education  |  -.6685418   .2360954    -2.83   0.005     -1.13128   -.2058033
                           Health  |  -.7160728     .23315    -3.07   0.002    -1.173038   -.2591071
                Natural Resources  |  -.6943929   .2077209    -3.34   0.001    -1.101518   -.2872675
             Environment & Energy  |  -.6791887   .2154278    -3.15   0.002    -1.101419    -.256958
             Economic Development  |  -.6486615   .2223899    -2.92   0.004    -1.084538   -.2127853
                 Criminal Justice  |  -.6984801   .2195309    -3.18   0.001    -1.128753   -.2682074
                       Regulatory  |  -.3828135   .2082881    -1.84   0.066    -.7910507    .0254237
                   Transportation  |   -.758484   .2349203    -3.23   0.001    -1.218919   -.2980487
                            Other  |  -.4179088   .2224198    -1.88   0.060    -.8538436    .0180259
                                   |
                             state |
                               AK  |  -.7021901   .3353398    -2.09   0.036    -1.359444   -.0449362
                               AZ  |  -.6088997   .3424955    -1.78   0.075    -1.280179    .0623792
                               AR  |  -1.150681   .3579351    -3.21   0.001    -1.852221   -.4491409
                               CA  |  -.2854144   .3939732    -0.72   0.469    -1.057588     .486759
                               CO  |  -.2645005   .3205356    -0.83   0.409    -.8927387    .3637377
                               CT  |  -.4325503   .3823997    -1.13   0.258     -1.18204    .3169393
                               DE  |  -.3475129   .3240393    -1.07   0.284    -.9826182    .2875924
                               FL  |  -.7937387   .3429178    -2.31   0.021    -1.465845   -.1216323
                               GA  |  -.4534919    .326765    -1.39   0.165     -1.09394    .1869557
                               HI  |  -1.212614    .370101    -3.28   0.001    -1.937999   -.4872298
                               ID  |  -.4420363   .3266577    -1.35   0.176    -1.082274     .198201
                               IL  |  -.6810352   .3858679    -1.76   0.078    -1.437322    .0752519
                               IN  |  -1.581135   .3780132    -4.18   0.000    -2.322027    -.840243
                               IA  |  -.6149251   .3101542    -1.98   0.047    -1.222816   -.0070339
                               KS  |  -.0454531   .3386194    -0.13   0.893     -.709135    .6182289
                               KY  |  -.9229367   .3618455    -2.55   0.011    -1.632141   -.2137325
                               LA  |  -.2613617   .3559067    -0.73   0.463    -.9589261    .4362027
                               ME  |  -.1422253   .3399747    -0.42   0.676    -.8085635    .5241129
                               MD  |  -.4782876   .3355941    -1.43   0.154     -1.13604    .1794646
                               MA  |   -.490273   .3692066    -1.33   0.184    -1.213905    .2333586
                               MI  |  -.9479689   .3362691    -2.82   0.005    -1.607044   -.2888936
                               MN  |  -.4225404   .3071593    -1.38   0.169    -1.024562    .1794808
                               MS  |   .2529645   .3500527     0.72   0.470    -.4331262    .9390552
                               MO  |  -.3785107   .3203291    -1.18   0.237    -1.006344    .2493228
                               MT  |  -.2498021   .3103891    -0.80   0.421    -.8581536    .3585493
                               NE  |  -1.155953   .3354028    -3.45   0.001    -1.813331   -.4985756
                               NV  |  -.7810891   .3276759    -2.38   0.017    -1.423322   -.1388562
                               NH  |  -.3923915   .3354171    -1.17   0.242    -1.049797    .2650139
                               NJ  |  -.9541988   .3573324    -2.67   0.008    -1.654558   -.2538401
                               NM  |  -.0117786   .3484259    -0.03   0.973    -.6946809    .6711237
                               NY  |  -1.104408   .4374462    -2.52   0.012    -1.961787   -.2470295
                               NC  |   -1.00072   .3083294    -3.25   0.001    -1.605034   -.3964052
                               ND  |  -.3958949    .317728    -1.25   0.213     -1.01863    .2268406
                               OH  |  -.6921162   .3188852    -2.17   0.030     -1.31712   -.0671126
                               OK  |  -.7462264   .3266396    -2.28   0.022    -1.386428   -.1060245
                               OR  |  -.2930649   .3191188    -0.92   0.358    -.9185262    .3323965
                               PA  |  -1.214162   .3483194    -3.49   0.000    -1.896855   -.5314681
                               RI  |  -.5435922   .3486856    -1.56   0.119    -1.227004    .1398191
                               SC  |  -.4386775   .3256425    -1.35   0.178    -1.076925    .1995701
                               SD  |  -.9790955   .3330273    -2.94   0.003    -1.631817    -.326374
                               TN  |  -.7985914   .3449734    -2.31   0.021    -1.474727    -.122456
                               TX  |   .1107158   .3421581     0.32   0.746    -.5599016    .7813333
                               UT  |  -.6661775    .310534    -2.15   0.032    -1.274813    -.057542
                               VT  |   -.755742   .3336127    -2.27   0.023    -1.409611   -.1018731
                               VA  |  -1.059931   .3733947    -2.84   0.005    -1.791771   -.3280904
                               WA  |  -.3372901    .324648    -1.04   0.299    -.9735885    .2990083
                               WV  |  -.8559027   .3358852    -2.55   0.011    -1.514226   -.1975799
                               WI  |  -.6827248   .3211004    -2.13   0.033     -1.31207   -.0533797
                               WY  |  -.4701363   .3261758    -1.44   0.149    -1.109429    .1691565
                                   |
                              year |
                             1984  |  -.0091605   .1315205    -0.07   0.944     -.266936     .248615
                             1988  |  -.1626781   .1238672    -1.31   0.189    -.4054534    .0800971
                             1994  |  -.3159516    .132148    -2.39   0.017    -.5749569   -.0569464
                             1998  |   -.574236   .1424795    -4.03   0.000    -.8534906   -.2949813
                             2004  |  -.2317981   .1444902    -1.60   0.109    -.5149936    .0513974
                             2008  |  -.5795583   .1553307    -3.73   0.000    -.8840008   -.2751157
                                   |
                             _cons |   .7295934   .9374358     0.78   0.436    -1.107747    2.566934
-----------------------------------+----------------------------------------------------------------
Moderate                           |  (base outcome)
-----------------------------------+----------------------------------------------------------------
High                               |
                      intersection |
                      White Woman  |  -.0923464   .1035691    -0.89   0.373    -.2953381    .1106454
                     Man of Color  |   .1302833   .1310047     0.99   0.320    -.1264813    .3870478
                   Woman of Color  |   .7918843    .235617     3.36   0.001     .3300835    1.253685
                                   |
                           reve_1a |
                Less than Monthly  |   .1309611   .1112179     1.18   0.239    -.0870219    .3489441
                          Monthly  |    .108209    .139705     0.77   0.439    -.1656078    .3820258
                           Weekly  |    .348655   .1674385     2.08   0.037     .0204816    .6768284
                            Daily  |   .4392066   .2810783     1.56   0.118    -.1116968      .99011
                                   |
                           reve_1b |
                Less than Monthly  |  -.3953847   .2556389    -1.55   0.122    -.8964276    .1056583
                          Monthly  |  -.3641636   .2637789    -1.38   0.167    -.8811607    .1528336
                           Weekly  |  -.2379743   .2681103    -0.89   0.375    -.7634608    .2875122
                            Daily  |  -.2177243   .2845699    -0.77   0.444    -.7754711    .3400225
                                   |
                     civil_service |
                              Yes  |   .1085627   .0907115     1.20   0.231    -.0692285    .2863539
                      weekly_hours |  -.0016091   .0045392    -0.35   0.723    -.0105058    .0072877
                               age |   .0299914   .0349456     0.86   0.391    -.0385008    .0984835
                             age_2 |  -.0002828   .0003523    -0.80   0.422    -.0009732    .0004076
                                   |
                               edu |
              High school or less  |   .2105034   .3148204     0.67   0.504    -.4065333      .82754
                     Some college  |  -.0644227   .1668077    -0.39   0.699    -.3913599    .2625144
                   Graduate study  |  -.1577402   .1161147    -1.36   0.174    -.3853209    .0698405
                  Graduate degree  |   -.176895   .0953761    -1.85   0.064    -.3638286    .0100386
                                   |
                years_employ_state |   .0055287   .0059761     0.93   0.355    -.0061842    .0172416
               years_employ_agency |  -.0031003    .006407    -0.48   0.628    -.0156578    .0094573
             years_employ_position |   -.000883   .0090915    -0.10   0.923    -.0187021    .0169361
                                   |
                              pid5 |
                       Republican  |   .3703402   .1221066     3.03   0.002     .1310157    .6096647
                  Lean Republican  |   .2948126    .157463     1.87   0.061    -.0138093    .6034345
                  Lean Democratic  |   .0556071   .1546758     0.36   0.719    -.2475518    .3587661
                       Democratic  |   .2679026   .1138703     2.35   0.019     .0447209    .4910844
                                   |
                       agency_size |
                           25-100  |  -.1687846   .1090339    -1.55   0.122    -.3824871     .044918
                          101-500  |  -.4342977   .1259048    -3.45   0.001    -.6810666   -.1875287
                        501-1,000  |  -.6065636   .1724903    -3.52   0.000    -.9446383   -.2684888
                      1,001-5,000  |  -.6175398    .173905    -3.55   0.000    -.9583875   -.2766922
                       Over 5,000  |  -.5613718   .2386026    -2.35   0.019    -1.029024   -.0937194
                                   |
                 log_agency_budget |  -.0352855   .0291526    -1.21   0.226    -.0924236    .0218525
                      inst6017_nom |   -.012905   .0044077    -2.93   0.003     -.021544   -.0042661
                                   |
                          funcat13 |
                    Staff: Fiscal  |   1.030129   .2787811     3.70   0.000     .4837279     1.57653
                Staff: Non-Fiscal  |   1.114688   .2799241     3.98   0.000     .5660466    1.663329
Income Security & Social Services  |   .5404339   .2746026     1.97   0.049     .0022226    1.078645
                        Education  |   .3211233   .3007454     1.07   0.286    -.2683269    .9105735
                           Health  |   .7261294    .285754     2.54   0.011     .1660619    1.286197
                Natural Resources  |   .4121009   .2663582     1.55   0.122    -.1099515    .9341534
             Environment & Energy  |   .6010954   .2694288     2.23   0.026     .0730246    1.129166
             Economic Development  |   .7645264   .2716012     2.81   0.005     .2321979    1.296855
                 Criminal Justice  |   .7670773   .2722508     2.82   0.005     .2334755    1.300679
                       Regulatory  |   .3645345   .2674704     1.36   0.173    -.1596978    .8887668
                   Transportation  |   .6918741   .2855659     2.42   0.015     .1321752    1.251573
                            Other  |   1.096799    .272465     4.03   0.000     .5627771     1.63082
                                   |
                             state |
                               AK  |   .4266568   .3375524     1.26   0.206    -.2349337    1.088247
                               AZ  |   .0056699   .3690387     0.02   0.988    -.7176326    .7289724
                               AR  |    -.01093   .3541169    -0.03   0.975    -.7049865    .6831264
                               CA  |   1.065983   .3994551     2.67   0.008     .2830654    1.848901
                               CO  |  -1.079794   .4063844    -2.66   0.008    -1.876293   -.2832955
                               CT  |  -.0203215   .4414046    -0.05   0.963    -.8854585    .8448155
                               DE  |  -.2111611   .3634439    -0.58   0.561     -.923498    .5011759
                               FL  |  -.1760699   .3701422    -0.48   0.634    -.9015354    .5493955
                               GA  |   -.065051   .3675644    -0.18   0.860    -.7854641    .6553621
                               HI  |   .1539233   .3476846     0.44   0.658     -.527526    .8353725
                               ID  |  -.3758961   .3573679    -1.05   0.293    -1.076324    .3245321
                               IL  |   .1057086   .3906449     0.27   0.787    -.6599414    .8713586
                               IN  |   .2332122   .3433955     0.68   0.497    -.4398305    .9062549
                               IA  |  -.3523456   .3493406    -1.01   0.313    -1.037041    .3323494
                               KS  |   .3052133   .3629756     0.84   0.400    -.4062058    1.016632
                               KY  |   .4901888    .355132     1.38   0.167    -.2058572    1.186235
                               LA  |   .2267625   .3783351     0.60   0.549    -.5147606    .9682857
                               ME  |  -.2753081   .3946646    -0.70   0.485    -1.048837    .4982203
                               MD  |   .3215334   .3630913     0.89   0.376    -.3901125    1.033179
                               MA  |   .5162029   .3918518     1.32   0.188    -.2518126    1.284218
                               MI  |   .1214446   .3482016     0.35   0.727    -.5610181    .8039073
                               MN  |  -.8644018   .3861583    -2.24   0.025    -1.621258   -.1075454
                               MS  |   .1352123   .4079488     0.33   0.740    -.6643526    .9347771
                               MO  |  -.1158332   .3634619    -0.32   0.750    -.8282055    .5965391
                               MT  |  -.2478233   .3489588    -0.71   0.478      -.93177    .4361233
                               NE  |  -.2931349   .3384126    -0.87   0.386    -.9564114    .3701417
                               NV  |  -.2823444   .3550715    -0.80   0.427    -.9782717     .413583
                               NH  |  -.7091246   .3756749    -1.89   0.059    -1.445434    .0271848
                               NJ  |   .4042132   .3654693     1.11   0.269    -.3120935     1.12052
                               NM  |    .335763   .3830977     0.88   0.381    -.4150948    1.086621
                               NY  |   .4388889   .3945213     1.11   0.266    -.3343586    1.212136
                               NC  |  -.3133781   .3335013    -0.94   0.347    -.9670286    .3402723
                               ND  |  -.3805223   .3582811    -1.06   0.288     -1.08274    .3216958
                               OH  |  -.2573145   .3551729    -0.72   0.469    -.9534406    .4388115
                               OK  |  -.0648796    .344908    -0.19   0.851    -.7408867    .6111276
                               OR  |  -.4155546   .3757579    -1.11   0.269    -1.152027    .3209174
                               PA  |   .3814675   .3438078     1.11   0.267    -.2923833    1.055318
                               RI  |   .0264847   .3772799     0.07   0.944    -.7129702    .7659397
                               SC  |  -.9811257   .4183889    -2.35   0.019    -1.801153   -.1610985
                               SD  |  -.3849616   .3496992    -1.10   0.271    -1.070359    .3004361
                               TN  |   .3007379   .3703775     0.81   0.417    -.4251886    1.026664
                               TX  |  -.2407132    .431369    -0.56   0.577    -1.086181    .6047546
                               UT  |   -.334638   .3344827    -1.00   0.317     -.990212    .3209361
                               VT  |  -.0910377   .3589446    -0.25   0.800    -.7945561    .6124807
                               VA  |   .4537124   .3722949     1.22   0.223    -.2759723    1.183397
                               WA  |  -.2284795   .3708602    -0.62   0.538    -.9553521    .4983931
                               WV  |  -.4459966   .3592617    -1.24   0.214    -1.150137    .2581434
                               WI  |  -.2077382   .3464059    -0.60   0.549    -.8866813    .4712048
                               WY  |   .3572819   .3418634     1.05   0.296     -.312758    1.027322
                                   |
                              year |
                             1984  |  -.3383818   .1331705    -2.54   0.011    -.5993911   -.0773725
                             1988  |   -.732128   .1276367    -5.74   0.000    -.9822914   -.4819646
                             1994  |  -.2761611    .131128    -2.11   0.035    -.5331672    -.019155
                             1998  |  -.3585438   .1384276    -2.59   0.010     -.629857   -.0872306
                             2004  |  -.7801046   .1538806    -5.07   0.000    -1.081705   -.4785042
                             2008  |  -.7446252   .1623762    -4.59   0.000    -1.062877   -.4263738
                                   |
                             _cons |   .0765455   .9778779     0.08   0.938     -1.84006    1.993151
----------------------------------------------------------------------------------------------------

. 
. est sto mlogit7

. 
.  esttab mlogit7 using Table_B14.rtf  ,starlevels(+ 0.10 * 0.05 ** 0.01) cells(b(star fmt(3)) se(par fmt(3))
> ) ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Gov. Regs." ) 
(output written to Table_B14.rtf)

. 
. 
. ***** CODE USED TO PRODUCE APPENDIX TABLE B15 ******
. mlogit d_21a i.intersection i.reve_1c i.reve_1d i.civil_service weekly_hours age age_2 b3.edu years_employ_
> state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fun
> cat13 i.state i.year , base(2) r 

Iteration 0:   log pseudolikelihood = -7690.3555  
Iteration 1:   log pseudolikelihood = -7353.8194  
Iteration 2:   log pseudolikelihood = -7277.7096  
Iteration 3:   log pseudolikelihood = -7274.9811  
Iteration 4:   log pseudolikelihood = -7274.9326  
Iteration 5:   log pseudolikelihood = -7274.9324  

Multinomial logistic regression                 Number of obs     =      6,158
                                                Wald chi2(300)    =     830.00
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -7274.9324               Pseudo R2         =     0.0540

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_21a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
None                               |
                      intersection |
                      White Woman  |   -.017811   .1864531    -0.10   0.924    -.3832524    .3476304
                     Man of Color  |  -.3036983   .2427656    -1.25   0.211    -.7795102    .1721136
                   Woman of Color  |  -.1542268   .4439368    -0.35   0.728    -1.024327    .7158732
                                   |
                           reve_1c |
                Less than Monthly  |  -.3410282   .3694842    -0.92   0.356    -1.065204    .3831476
                          Monthly  |  -.3853745   .3866377    -1.00   0.319    -1.143171    .3724215
                           Weekly  |  -.5327549   .4051969    -1.31   0.189    -1.326926    .2614164
                            Daily  |  -.1773968   .4783508    -0.37   0.711    -1.114947    .7601535
                                   |
                           reve_1d |
                Less than Monthly  |  -1.391634   .2725036    -5.11   0.000    -1.925731   -.8575368
                          Monthly  |  -1.780756   .2883901    -6.17   0.000    -2.345991   -1.215522
                           Weekly  |  -1.929555   .3111119    -6.20   0.000    -2.539323   -1.319787
                            Daily  |  -1.828935   .3925035    -4.66   0.000    -2.598228   -1.059642
                                   |
                     civil_service |
                              Yes  |  -.1685467   .1589076    -1.06   0.289    -.4799999    .1429064
                      weekly_hours |   .0016573   .0075978     0.22   0.827    -.0132342    .0165487
                               age |   .0448116   .0559643     0.80   0.423    -.0648763    .1544996
                             age_2 |  -.0003944   .0005479    -0.72   0.472    -.0014682    .0006794
                                   |
                               edu |
              High school or less  |   .2490657    .529819     0.47   0.638    -.7893604    1.287492
                     Some college  |   .3636401   .2656053     1.37   0.171    -.1569368     .884217
                   Graduate study  |  -.1076852   .2200809    -0.49   0.625    -.5390359    .3236655
                  Graduate degree  |    .182702   .1639752     1.11   0.265    -.1386835    .5040875
                                   |
                years_employ_state |    -.01062   .0102945    -1.03   0.302    -.0307969    .0095568
               years_employ_agency |   .0132593   .0114925     1.15   0.249    -.0092656    .0357843
             years_employ_position |    .037493    .014603     2.57   0.010     .0088716    .0661143
                                   |
                              pid5 |
                       Republican  |   .0242084   .2017311     0.12   0.904    -.3711773    .4195941
                  Lean Republican  |   -.085071   .2673313    -0.32   0.750    -.6090306    .4388887
                  Lean Democratic  |  -.5457815   .2980643    -1.83   0.067    -1.129977    .0384138
                       Democratic  |  -.1286361   .1890675    -0.68   0.496    -.4992015    .2419293
                                   |
                       agency_size |
                           25-100  |  -.4871597   .1724077    -2.83   0.005    -.8250726   -.1492468
                          101-500  |  -.5485222   .2092188    -2.62   0.009    -.9585835    -.138461
                        501-1,000  |  -.5292999   .2960186    -1.79   0.074    -1.109486    .0508859
                      1,001-5,000  |  -.5375169   .3170494    -1.70   0.090    -1.158922    .0838886
                       Over 5,000  |   -.808882   .4809669    -1.68   0.093     -1.75156    .1337958
                                   |
                 log_agency_budget |  -.1173671    .051769    -2.27   0.023    -.2188325   -.0159016
                      inst6017_nom |  -.0137162   .0080048    -1.71   0.087    -.0294053    .0019728
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -1.117453   .3505937    -3.19   0.001    -1.804604    -.430302
                Staff: Non-Fiscal  |  -.9185919   .3317216    -2.77   0.006    -1.568754   -.2684294
Income Security & Social Services  |  -1.085052   .3306387    -3.28   0.001    -1.733092   -.4370124
                        Education  |  -1.093173   .3588784    -3.05   0.002    -1.796561   -.3897838
                           Health  |   -1.64214   .4054079    -4.05   0.000    -2.436725   -.8475555
                Natural Resources  |  -2.166654   .3401205    -6.37   0.000    -2.833278    -1.50003
             Environment & Energy  |  -1.765312   .3311398    -5.33   0.000    -2.414334    -1.11629
             Economic Development  |  -.9495563   .3114587    -3.05   0.002    -1.560004   -.3391085
                 Criminal Justice  |  -.6607736   .2935622    -2.25   0.024    -1.236145   -.0854022
                       Regulatory  |  -.9603165   .2711498    -3.54   0.000     -1.49176   -.4288726
                   Transportation  |  -1.586734    .364571    -4.35   0.000     -2.30128    -.872188
                            Other  |  -.8846441   .2917869    -3.03   0.002    -1.456536   -.3127523
                                   |
                             state |
                               AK  |  -.6903132   .5267032    -1.31   0.190    -1.722633    .3420062
                               AZ  |  -.1474157    .503791    -0.29   0.770    -1.134828    .8399966
                               AR  |  -.3423027   .5064208    -0.68   0.499    -1.334869    .6502638
                               CA  |  -.4598623   .6091474    -0.75   0.450    -1.653769    .7340447
                               CO  |  -.3536561   .4908642    -0.72   0.471    -1.315732    .6084201
                               CT  |   .0541763    .594947     0.09   0.927    -1.111898    1.220251
                               DE  |  -.5886232   .5096561    -1.15   0.248    -1.587531    .4102844
                               FL  |   -.510724   .5916034    -0.86   0.388    -1.670245    .6487973
                               GA  |  -.2274635   .5005662    -0.45   0.650    -1.208555    .7536283
                               HI  |   .1702578   .4979169     0.34   0.732    -.8056415    1.146157
                               ID  |  -2.085057   .7004533    -2.98   0.003     -3.45792   -.7121941
                               IL  |  -.5976584   .5671637    -1.05   0.292    -1.709279     .513962
                               IN  |  -.3657294   .4799424    -0.76   0.446    -1.306399    .5749405
                               IA  |  -3.316278   1.082159    -3.06   0.002    -5.437271   -1.195286
                               KS  |  -1.276077   .6149773    -2.07   0.038     -2.48141   -.0707433
                               KY  |  -1.312366    .692646    -1.89   0.058    -2.669927    .0451949
                               LA  |  -.6626994   .6577935    -1.01   0.314    -1.951951    .6265522
                               ME  |  -.7239045   .6067563    -1.19   0.233    -1.913125     .465316
                               MD  |  -.1195883   .5307078    -0.23   0.822    -1.159756    .9205799
                               MA  |  -.3096418   .5749561    -0.54   0.590    -1.436535    .8172515
                               MI  |  -1.543844   .7823969    -1.97   0.048    -3.077314   -.0103747
                               MN  |  -.3986748   .5288773    -0.75   0.451    -1.435255    .6379056
                               MS  |  -.1576582    .455191    -0.35   0.729    -1.049816    .7344997
                               MO  |  -.8350976   .5193181    -1.61   0.108    -1.852942    .1827472
                               MT  |  -.6070976    .469491    -1.29   0.196    -1.527283    .3130878
                               NE  |  -.5982198   .5150873    -1.16   0.245    -1.607772    .4113328
                               NV  |  -.3092612   .5060416    -0.61   0.541    -1.301085    .6825622
                               NH  |  -1.455801   .5840224    -2.49   0.013    -2.600464   -.3111381
                               NJ  |  -.4155789   .5332017    -0.78   0.436    -1.460635    .6294772
                               NM  |   .2830655   .4824191     0.59   0.557    -.6624586     1.22859
                               NY  |  -.4057351   .5621076    -0.72   0.470    -1.507446    .6959756
                               NC  |  -.2712262   .4520856    -0.60   0.549    -1.157298    .6148452
                               ND  |  -1.089032   .5033172    -2.16   0.030    -2.075516   -.1025488
                               OH  |  -.8408703   .5547779    -1.52   0.130    -1.928215    .2464744
                               OK  |  -.6795451   .5171838    -1.31   0.189    -1.693207    .3341166
                               OR  |  -1.700631    .819408    -2.08   0.038    -3.306641   -.0946204
                               PA  |  -.0920574   .5100428    -0.18   0.857    -1.091723    .9076082
                               RI  |  -.5837534   .5581753    -1.05   0.296    -1.677757    .5102502
                               SC  |   -.165971   .5327526    -0.31   0.755    -1.210147    .8782049
                               SD  |  -.4601434    .459417    -1.00   0.317    -1.360584    .4402975
                               TN  |  -1.570918   .8046374    -1.95   0.051    -3.147978    .0061423
                               TX  |  -.2806936   .5447297    -0.52   0.606    -1.348344     .786957
                               UT  |  -1.131037    .517961    -2.18   0.029    -2.146222    -.115852
                               VT  |  -1.545513   .6347245    -2.43   0.015     -2.78955    -.301476
                               VA  |  -.5815769   .6016576    -0.97   0.334    -1.760804    .5976505
                               WA  |  -.1363871   .5192421    -0.26   0.793    -1.154083    .8813087
                               WV  |   -.775269   .5663308    -1.37   0.171    -1.885257     .334719
                               WI  |  -1.621162   .6537849    -2.48   0.013    -2.902557   -.3397671
                               WY  |  -.6794787   .4639857    -1.46   0.143    -1.588874    .2299165
                                   |
                              year |
                             1984  |  -.5285764   .2150167    -2.46   0.014    -.9500014   -.1071513
                             1988  |  -.5234595    .207591    -2.52   0.012    -.9303304   -.1165887
                             1994  |  -.5032059   .2117475    -2.38   0.017    -.9182235   -.0881884
                             1998  |  -.9167036   .2361937    -3.88   0.000    -1.379635   -.4537725
                             2004  |  -.4531254   .2399868    -1.89   0.059     -.923491    .0172402
                             2008  |  -1.221461   .2987064    -4.09   0.000    -1.806915   -.6360072
                                   |
                             _cons |   2.436335    1.54558     1.58   0.115    -.5929455    5.465616
-----------------------------------+----------------------------------------------------------------
Slight                             |
                      intersection |
                      White Woman  |   .1931054   .0911025     2.12   0.034     .0145478    .3716631
                     Man of Color  |  -.3172519   .1313955    -2.41   0.016    -.5747823   -.0597214
                   Woman of Color  |  -.1812307   .2552353    -0.71   0.478    -.6814826    .3190213
                                   |
                           reve_1c |
                Less than Monthly  |   -.297629   .3278281    -0.91   0.364    -.9401602    .3449022
                          Monthly  |  -.1161711   .3310821    -0.35   0.726      -.76508    .5327378
                           Weekly  |  -.2485277   .3366195    -0.74   0.460    -.9082898    .4112343
                            Daily  |  -.4385847   .3601172    -1.22   0.223    -1.144402    .2672321
                                   |
                           reve_1d |
                Less than Monthly  |   .0999562   .2365576     0.42   0.673    -.3636882    .5636006
                          Monthly  |   -.047279   .2385816    -0.20   0.843    -.5148903    .4203324
                           Weekly  |   -.095447   .2438756    -0.39   0.696    -.5734344    .3825405
                            Daily  |  -.2652661   .2801941    -0.95   0.344    -.8144364    .2839041
                                   |
                     civil_service |
                              Yes  |  -.0358238    .081392    -0.44   0.660    -.1953493    .1237017
                      weekly_hours |   -.001208   .0040723    -0.30   0.767    -.0091895    .0067735
                               age |   .0356844   .0334236     1.07   0.286    -.0298247    .1011934
                             age_2 |  -.0003552   .0003354    -1.06   0.290    -.0010126    .0003023
                                   |
                               edu |
              High school or less  |  -.0919749   .3427269    -0.27   0.788    -.7637072    .5797574
                     Some college  |   .1663849   .1599225     1.04   0.298    -.1470575    .4798274
                   Graduate study  |   .2015898   .1124731     1.79   0.073    -.0188535     .422033
                  Graduate degree  |   .1884617   .0906195     2.08   0.038     .0108507    .3660726
                                   |
                years_employ_state |   .0071847   .0054888     1.31   0.191    -.0035731    .0179426
               years_employ_agency |  -.0004943   .0058017    -0.09   0.932    -.0118654    .0108769
             years_employ_position |   .0013891   .0076752     0.18   0.856    -.0136541    .0164322
                                   |
                              pid5 |
                       Republican  |   .2498545   .1123171     2.22   0.026     .0297171    .4699919
                  Lean Republican  |   .0759571   .1469261     0.52   0.605    -.2120127     .363927
                  Lean Democratic  |   .0029166   .1401706     0.02   0.983    -.2718127    .2776459
                       Democratic  |   .1194994   .1045907     1.14   0.253    -.0854945    .3244933
                                   |
                       agency_size |
                           25-100  |  -.0985542   .1047592    -0.94   0.347    -.3038784      .10677
                          101-500  |  -.0128661   .1183491    -0.11   0.913     -.244826    .2190938
                        501-1,000  |   .0711462    .154941     0.46   0.646    -.2325326     .374825
                      1,001-5,000  |   .0620516   .1636458     0.38   0.705    -.2586883    .3827915
                       Over 5,000  |   .2396354   .2167899     1.11   0.269     -.185265    .6645357
                                   |
                 log_agency_budget |  -.0130779   .0271604    -0.48   0.630    -.0663113    .0401554
                      inst6017_nom |   .0006121   .0040558     0.15   0.880    -.0073371    .0085612
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.2549457    .212338    -1.20   0.230    -.6711206    .1612292
                Staff: Non-Fiscal  |  -.2889992   .2214988    -1.30   0.192    -.7231288    .1451304
Income Security & Social Services  |  -.3139752   .2033325    -1.54   0.123    -.7124996    .0845491
                        Education  |  -.3345463   .2215776    -1.51   0.131    -.7688304    .0997377
                           Health  |  -.2827446   .2154162    -1.31   0.189    -.7049525    .1394634
                Natural Resources  |  -.3408905   .1922803    -1.77   0.076    -.7177528    .0359719
             Environment & Energy  |  -.4688997   .2016218    -2.33   0.020    -.8640712   -.0737283
             Economic Development  |  -.1958207   .2044276    -0.96   0.338    -.5964914    .2048501
                 Criminal Justice  |  -.1134698   .2018796    -0.56   0.574    -.5091466    .2822069
                       Regulatory  |  -.1317981   .1908645    -0.69   0.490    -.5058857    .2422895
                   Transportation  |  -.4605179   .2185867    -2.11   0.035    -.8889399   -.0320958
                            Other  |  -.2868649   .2050736    -1.40   0.162    -.6888019     .115072
                                   |
                             state |
                               AK  |  -.1110527   .2987061    -0.37   0.710     -.696506    .4744005
                               AZ  |   .1405429   .3163309     0.44   0.657    -.4794543      .76054
                               AR  |  -.7030017   .3419297    -2.06   0.040    -1.373172   -.0328318
                               CA  |   -.009462   .3245934    -0.03   0.977    -.6456533    .6267293
                               CO  |   .1083198   .2931142     0.37   0.712    -.4661734    .6828131
                               CT  |  -.7461931   .4034302    -1.85   0.064    -1.536902    .0445156
                               DE  |  -.0241489   .3077492    -0.08   0.937    -.6273262    .5790283
                               FL  |  -.3358405   .3258297    -1.03   0.303    -.9744549    .3027739
                               GA  |  -.1465902   .3058805    -0.48   0.632     -.746105    .4529245
                               HI  |    .312427   .3194981     0.98   0.328    -.3137779    .9386318
                               ID  |  -.2341008   .3095778    -0.76   0.450    -.8408621    .3726605
                               IL  |  -.4003174   .3408384    -1.17   0.240    -1.068348    .2677136
                               IN  |  -.1617015   .3137702    -0.52   0.606    -.7766797    .4532767
                               IA  |  -.8177759   .3033016    -2.70   0.007    -1.412236   -.2233157
                               KS  |  -.1594266    .315603    -0.51   0.613    -.7779972     .459144
                               KY  |  -.7982937   .3418624    -2.34   0.020    -1.468332   -.1282557
                               LA  |   .0200808   .3346946     0.06   0.952    -.6359085    .6760702
                               ME  |   .0505133    .323583     0.16   0.876    -.5836977    .6847244
                               MD  |  -.2565998   .3165204    -0.81   0.418    -.8769684    .3637689
                               MA  |    -.27887   .3273374    -0.85   0.394    -.9204395    .3626995
                               MI  |  -.3939444   .3255212    -1.21   0.226    -1.031954    .2440654
                               MN  |   .0614868   .2905171     0.21   0.832    -.5079163    .6308899
                               MS  |  -.3958789   .3194549    -1.24   0.215    -1.021999    .2302411
                               MO  |   -.072186   .2941233    -0.25   0.806    -.6486571    .5042852
                               MT  |   .0997507   .2845607     0.35   0.726     -.457978    .6574793
                               NE  |   .2406174   .3043579     0.79   0.429    -.3559131    .8371479
                               NV  |   -.220146   .3089185    -0.71   0.476    -.8256152    .3853231
                               NH  |  -.6815846   .3449729    -1.98   0.048    -1.357719   -.0054502
                               NJ  |   -.326044   .3268392    -1.00   0.318     -.966637    .3145491
                               NM  |   .5235733   .3225473     1.62   0.105    -.1086078    1.155754
                               NY  |  -.4246594   .3707751    -1.15   0.252    -1.151365    .3020464
                               NC  |  -.1086878   .2870406    -0.38   0.705    -.6712771    .4539015
                               ND  |  -.0168033   .2961837    -0.06   0.955    -.5973127    .5637062
                               OH  |  -.2258414   .3079669    -0.73   0.463    -.8294454    .3777625
                               OK  |  -.5028335   .3165059    -1.59   0.112    -1.123174    .1175068
                               OR  |   .1901156   .2992265     0.64   0.525    -.3963576    .7765888
                               PA  |   -.088561    .308927    -0.29   0.774    -.6940467    .5169248
                               RI  |   .0705929    .323623     0.22   0.827    -.5636966    .7048824
                               SC  |  -.0985969   .3491242    -0.28   0.778    -.7828677     .585674
                               SD  |  -.0310379   .3100202    -0.10   0.920    -.6386664    .5765906
                               TN  |  -.4553924   .3257422    -1.40   0.162    -1.093835    .1830505
                               TX  |  -.1851055   .3319583    -0.56   0.577    -.8357318    .4655209
                               UT  |  -.0385934   .2943744    -0.13   0.896    -.6155567    .5383699
                               VT  |  -.6401209   .3229333    -1.98   0.047    -1.273059   -.0071832
                               VA  |   .0359084   .3338692     0.11   0.914    -.6184632    .6902801
                               WA  |  -.0699178   .2990982    -0.23   0.815    -.6561395     .516304
                               WV  |  -1.040264   .3477999    -2.99   0.003    -1.721939   -.3585887
                               WI  |  -.7433158   .3180142    -2.34   0.019    -1.366612   -.1200194
                               WY  |  -.1365729   .2961266    -0.46   0.645    -.7169703    .4438245
                                   |
                              year |
                             1984  |  -.1254798   .1215138    -1.03   0.302    -.3636425    .1126829
                             1988  |  -.0681856   .1150611    -0.59   0.553    -.2937012    .1573301
                             1994  |    -.40227   .1236657    -3.25   0.001    -.6446503   -.1598897
                             1998  |  -.5180192   .1332519    -3.89   0.000    -.7791881   -.2568503
                             2004  |  -.2018137   .1360086    -1.48   0.138    -.4683858    .0647583
                             2008  |  -.5457735   .1470644    -3.71   0.000    -.8340144   -.2575326
                                   |
                             _cons |  -.3536101   .9487088    -0.37   0.709    -2.213045    1.505825
-----------------------------------+----------------------------------------------------------------
Moderate                           |  (base outcome)
-----------------------------------+----------------------------------------------------------------
High                               |
                      intersection |
                      White Woman  |   .0440057   .1006857     0.44   0.662    -.1533346    .2413461
                     Man of Color  |   .1584426   .1310608     1.21   0.227    -.0984319    .4153171
                   Woman of Color  |   .5753669    .226474     2.54   0.011      .131486    1.019248
                                   |
                           reve_1c |
                Less than Monthly  |  -.4459402   .3199304    -1.39   0.163    -1.072992    .1811117
                          Monthly  |  -.4042144   .3242006    -1.25   0.212    -1.039636    .2312071
                           Weekly  |  -.4561308   .3327556    -1.37   0.170     -1.10832    .1960581
                            Daily  |  -.5963898   .3578929    -1.67   0.096    -1.297847    .1050674
                                   |
                           reve_1d |
                Less than Monthly  |   .2030139   .2680226     0.76   0.449    -.3223007    .7283285
                          Monthly  |    .239482   .2712833     0.88   0.377    -.2922235    .7711875
                           Weekly  |   .2777453   .2782552     1.00   0.318    -.2676247    .8231154
                            Daily  |   .4851151   .3077392     1.58   0.115    -.1180426    1.088273
                                   |
                     civil_service |
                              Yes  |   .0632999   .0874298     0.72   0.469    -.1080592    .2346591
                      weekly_hours |   .0017732    .004355     0.41   0.684    -.0067624    .0103088
                               age |   .0068649   .0324415     0.21   0.832    -.0567193    .0704492
                             age_2 |   .0000189   .0003219     0.06   0.953     -.000612    .0006498
                                   |
                               edu |
              High school or less  |   .4089992   .3129353     1.31   0.191    -.2043426    1.022341
                     Some college  |  -.0628759    .163315    -0.38   0.700    -.3829673    .2572156
                   Graduate study  |   .0108838   .1148016     0.09   0.924    -.2141233    .2358909
                  Graduate degree  |  -.1977874    .092681    -2.13   0.033    -.3794388   -.0161361
                                   |
                years_employ_state |  -.0042184   .0059338    -0.71   0.477    -.0158485    .0074117
               years_employ_agency |   .0125696   .0062527     2.01   0.044     .0003146    .0248246
             years_employ_position |  -.0085362   .0083067    -1.03   0.304     -.024817    .0077446
                                   |
                              pid5 |
                       Republican  |     .19353   .1184696     1.63   0.102    -.0386662    .4257263
                  Lean Republican  |   .2112893   .1539374     1.37   0.170    -.0904224     .513001
                  Lean Democratic  |   .0635601   .1482564     0.43   0.668    -.2270171    .3541373
                       Democratic  |   .0928747   .1102399     0.84   0.400    -.1231915    .3089408
                                   |
                       agency_size |
                           25-100  |  -.0796278   .1071074    -0.74   0.457    -.2895543    .1302988
                          101-500  |  -.0446499   .1243843    -0.36   0.720    -.2884388    .1991389
                        501-1,000  |  -.2803132   .1699149    -1.65   0.099    -.6133402    .0527138
                      1,001-5,000  |  -.3122494   .1719852    -1.82   0.069    -.6493342    .0248353
                       Over 5,000  |  -.2014075   .2365093    -0.85   0.394    -.6649573    .2621423
                                   |
                 log_agency_budget |  -.0135438   .0291429    -0.46   0.642    -.0706628    .0435752
                      inst6017_nom |    .003015   .0042384     0.71   0.477    -.0052922    .0113221
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.3520702     .21882    -1.61   0.108    -.7809495    .0768091
                Staff: Non-Fiscal  |  -.1545559    .223088    -0.69   0.488    -.5918002    .2826885
Income Security & Social Services  |   -.514735   .2097348    -2.45   0.014    -.9258077   -.1036624
                        Education  |  -.4555453   .2319942    -1.96   0.050    -.9102456    -.000845
                           Health  |   -.359459   .2234217    -1.61   0.108    -.7973575    .0784395
                Natural Resources  |  -.4261568   .1973025    -2.16   0.031    -.8128626    -.039451
             Environment & Energy  |  -.3384106   .2026145    -1.67   0.095    -.7355277    .0587065
             Economic Development  |  -.3939851   .2112157    -1.87   0.062    -.8079603    .0199902
                 Criminal Justice  |   -.408241   .2139006    -1.91   0.056    -.8274784    .0109964
                       Regulatory  |  -.4475014   .1965566    -2.28   0.023    -.8327452   -.0622577
                   Transportation  |  -.3620429   .2225965    -1.63   0.104    -.7983239    .0742382
                            Other  |  -.1991114   .2067546    -0.96   0.336    -.6043429    .2061201
                                   |
                             state |
                               AK  |  -.1213028   .3595982    -0.34   0.736    -.8261024    .5834968
                               AZ  |   .3747858   .3753902     1.00   0.318    -.3609654    1.110537
                               AR  |     .45121   .3485092     1.29   0.195    -.2318556    1.134276
                               CA  |   .0384826   .3885707     0.10   0.921    -.7231019    .8000671
                               CO  |  -.0402995   .3618316    -0.11   0.911    -.7494763    .6688774
                               CT  |   .6751274   .3919299     1.72   0.085    -.0930412    1.443296
                               DE  |   .0907284   .3637534     0.25   0.803    -.6222153     .803672
                               FL  |   .4094755   .3661316     1.12   0.263    -.3081292     1.12708
                               GA  |   .1035124   .3695226     0.28   0.779    -.6207386    .8277635
                               HI  |  -.1384272   .3906372    -0.35   0.723     -.904062    .6272076
                               ID  |   .5784869   .3457086     1.67   0.094    -.0990895    1.256063
                               IL  |  -.0301672   .3944517    -0.08   0.939    -.8032782    .7429439
                               IN  |   .1425247   .3708084     0.38   0.701    -.5842464    .8692958
                               IA  |   .1275465   .3330927     0.38   0.702    -.5253032    .7803963
                               KS  |   .9662545   .3396679     2.84   0.004     .3005177    1.631991
                               KY  |   .5900101   .3465348     1.70   0.089    -.0891856    1.269206
                               LA  |   .4661638   .3785036     1.23   0.218    -.2756897    1.208017
                               ME  |   .2459382   .3745062     0.66   0.511    -.4880805     .979957
                               MD  |   .5913066    .347372     1.70   0.089    -.0895301    1.272143
                               MA  |  -1.252537   .5196094    -2.41   0.016    -2.270953   -.2341213
                               MI  |   .7229411   .3394442     2.13   0.033     .0576428    1.388239
                               MN  |   .0191678   .3578157     0.05   0.957    -.6821381    .7204736
                               MS  |    .356133    .354783     1.00   0.315     -.339229    1.051495
                               MO  |   .0298431     .35175     0.08   0.932    -.6595742    .7192604
                               MT  |  -.0769508   .3531169    -0.22   0.827    -.7690472    .6151455
                               NE  |   .3568912   .3579318     1.00   0.319    -.3446422    1.058425
                               NV  |   .2663826   .3553359     0.75   0.453    -.4300629    .9628281
                               NH  |   .6968599   .3504431     1.99   0.047     .0100041    1.383716
                               NJ  |   .2099864   .3713307     0.57   0.572    -.5178085    .9377812
                               NM  |   .0836396   .4017426     0.21   0.835    -.7037614    .8710407
                               NY  |  -.3208387   .4472303    -0.72   0.473    -1.197394    .5557167
                               NC  |   .4923408   .3314326     1.49   0.137    -.1572552    1.141937
                               ND  |   .0372027   .3584249     0.10   0.917    -.6652972    .7397025
                               OH  |    .526795    .343952     1.53   0.126    -.1473386    1.200929
                               OK  |   .5761296   .3351569     1.72   0.086    -.0807659    1.233025
                               OR  |  -.0674065   .3793797    -0.18   0.859    -.8109771    .6761641
                               PA  |     .24146   .3613473     0.67   0.504    -.4667676    .9496876
                               RI  |  -.1249861   .4125732    -0.30   0.762    -.9336147    .6836425
                               SC  |   1.307201   .3583786     3.65   0.000     .6047923     2.00961
                               SD  |    .238211   .3662778     0.65   0.515    -.4796803    .9561022
                               TN  |   .4892328   .3551645     1.38   0.168    -.2068768    1.185342
                               TX  |   .7116582   .3611443     1.97   0.049     .0038284    1.419488
                               UT  |   .3860174   .3394661     1.14   0.255    -.2793239    1.051359
                               VT  |   .2487935   .3504074     0.71   0.478    -.4379924    .9355795
                               VA  |   .4787785   .3833785     1.25   0.212    -.2726296    1.230187
                               WA  |  -.5494796   .3939016    -1.39   0.163    -1.321513    .2225535
                               WV  |   .5293269   .3404098     1.55   0.120     -.137864    1.196518
                               WI  |   .2790964   .3343426     0.83   0.404     -.376203    .9343958
                               WY  |    .294355   .3417626     0.86   0.389    -.3754874    .9641975
                                   |
                              year |
                             1984  |  -.6035551    .129688    -4.65   0.000     -.857739   -.3493713
                             1988  |  -.4992408   .1224559    -4.08   0.000      -.73925   -.2592315
                             1994  |   -.377422   .1256017    -3.00   0.003    -.6235967   -.1312472
                             1998  |  -.3657484   .1337493    -2.73   0.006    -.6278921   -.1036047
                             2004  |  -.5514277   .1474916    -3.74   0.000     -.840506   -.2623494
                             2008  |  -.4487024   .1514133    -2.96   0.003     -.745467   -.1519379
                                   |
                             _cons |  -.2792973   .9505463    -0.29   0.769    -2.142334    1.583739
----------------------------------------------------------------------------------------------------

. 
. est sto mlogit8

. 
.  esttab mlogit8 using Table_B12.rtf  ,starlevels(+ 0.10 * 0.05 ** 0.01) cells(b(star fmt(3)) se(par fmt(3))
> ) ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Legis. Regs." ) 
file Table_B12.rtf already exists
r(602);

end of do-file

r(602);

. do "C:\Users\MUTTER~1\AppData\Local\Temp\STD74a8_000000.tmp"

. mlogit d_21a i.intersection i.reve_1c i.reve_1d i.civil_service weekly_hours age age_2 b3.edu years_employ_
> state years_employ_agency years_employ_position b3.pid5 i.agency_size log_agency_budget inst6017_nom  i.fun
> cat13 i.state i.year , base(2) r 

Iteration 0:   log pseudolikelihood = -7690.3555  
Iteration 1:   log pseudolikelihood = -7353.8194  
Iteration 2:   log pseudolikelihood = -7277.7096  
Iteration 3:   log pseudolikelihood = -7274.9811  
Iteration 4:   log pseudolikelihood = -7274.9326  
Iteration 5:   log pseudolikelihood = -7274.9324  

Multinomial logistic regression                 Number of obs     =      6,158
                                                Wald chi2(300)    =     830.00
                                                Prob > chi2       =     0.0000
Log pseudolikelihood = -7274.9324               Pseudo R2         =     0.0540

----------------------------------------------------------------------------------------------------
                                   |               Robust
                             d_21a |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-----------------------------------+----------------------------------------------------------------
None                               |
                      intersection |
                      White Woman  |   -.017811   .1864531    -0.10   0.924    -.3832524    .3476304
                     Man of Color  |  -.3036983   .2427656    -1.25   0.211    -.7795102    .1721136
                   Woman of Color  |  -.1542268   .4439368    -0.35   0.728    -1.024327    .7158732
                                   |
                           reve_1c |
                Less than Monthly  |  -.3410282   .3694842    -0.92   0.356    -1.065204    .3831476
                          Monthly  |  -.3853745   .3866377    -1.00   0.319    -1.143171    .3724215
                           Weekly  |  -.5327549   .4051969    -1.31   0.189    -1.326926    .2614164
                            Daily  |  -.1773968   .4783508    -0.37   0.711    -1.114947    .7601535
                                   |
                           reve_1d |
                Less than Monthly  |  -1.391634   .2725036    -5.11   0.000    -1.925731   -.8575368
                          Monthly  |  -1.780756   .2883901    -6.17   0.000    -2.345991   -1.215522
                           Weekly  |  -1.929555   .3111119    -6.20   0.000    -2.539323   -1.319787
                            Daily  |  -1.828935   .3925035    -4.66   0.000    -2.598228   -1.059642
                                   |
                     civil_service |
                              Yes  |  -.1685467   .1589076    -1.06   0.289    -.4799999    .1429064
                      weekly_hours |   .0016573   .0075978     0.22   0.827    -.0132342    .0165487
                               age |   .0448116   .0559643     0.80   0.423    -.0648763    .1544996
                             age_2 |  -.0003944   .0005479    -0.72   0.472    -.0014682    .0006794
                                   |
                               edu |
              High school or less  |   .2490657    .529819     0.47   0.638    -.7893604    1.287492
                     Some college  |   .3636401   .2656053     1.37   0.171    -.1569368     .884217
                   Graduate study  |  -.1076852   .2200809    -0.49   0.625    -.5390359    .3236655
                  Graduate degree  |    .182702   .1639752     1.11   0.265    -.1386835    .5040875
                                   |
                years_employ_state |    -.01062   .0102945    -1.03   0.302    -.0307969    .0095568
               years_employ_agency |   .0132593   .0114925     1.15   0.249    -.0092656    .0357843
             years_employ_position |    .037493    .014603     2.57   0.010     .0088716    .0661143
                                   |
                              pid5 |
                       Republican  |   .0242084   .2017311     0.12   0.904    -.3711773    .4195941
                  Lean Republican  |   -.085071   .2673313    -0.32   0.750    -.6090306    .4388887
                  Lean Democratic  |  -.5457815   .2980643    -1.83   0.067    -1.129977    .0384138
                       Democratic  |  -.1286361   .1890675    -0.68   0.496    -.4992015    .2419293
                                   |
                       agency_size |
                           25-100  |  -.4871597   .1724077    -2.83   0.005    -.8250726   -.1492468
                          101-500  |  -.5485222   .2092188    -2.62   0.009    -.9585835    -.138461
                        501-1,000  |  -.5292999   .2960186    -1.79   0.074    -1.109486    .0508859
                      1,001-5,000  |  -.5375169   .3170494    -1.70   0.090    -1.158922    .0838886
                       Over 5,000  |   -.808882   .4809669    -1.68   0.093     -1.75156    .1337958
                                   |
                 log_agency_budget |  -.1173671    .051769    -2.27   0.023    -.2188325   -.0159016
                      inst6017_nom |  -.0137162   .0080048    -1.71   0.087    -.0294053    .0019728
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -1.117453   .3505937    -3.19   0.001    -1.804604    -.430302
                Staff: Non-Fiscal  |  -.9185919   .3317216    -2.77   0.006    -1.568754   -.2684294
Income Security & Social Services  |  -1.085052   .3306387    -3.28   0.001    -1.733092   -.4370124
                        Education  |  -1.093173   .3588784    -3.05   0.002    -1.796561   -.3897838
                           Health  |   -1.64214   .4054079    -4.05   0.000    -2.436725   -.8475555
                Natural Resources  |  -2.166654   .3401205    -6.37   0.000    -2.833278    -1.50003
             Environment & Energy  |  -1.765312   .3311398    -5.33   0.000    -2.414334    -1.11629
             Economic Development  |  -.9495563   .3114587    -3.05   0.002    -1.560004   -.3391085
                 Criminal Justice  |  -.6607736   .2935622    -2.25   0.024    -1.236145   -.0854022
                       Regulatory  |  -.9603165   .2711498    -3.54   0.000     -1.49176   -.4288726
                   Transportation  |  -1.586734    .364571    -4.35   0.000     -2.30128    -.872188
                            Other  |  -.8846441   .2917869    -3.03   0.002    -1.456536   -.3127523
                                   |
                             state |
                               AK  |  -.6903132   .5267032    -1.31   0.190    -1.722633    .3420062
                               AZ  |  -.1474157    .503791    -0.29   0.770    -1.134828    .8399966
                               AR  |  -.3423027   .5064208    -0.68   0.499    -1.334869    .6502638
                               CA  |  -.4598623   .6091474    -0.75   0.450    -1.653769    .7340447
                               CO  |  -.3536561   .4908642    -0.72   0.471    -1.315732    .6084201
                               CT  |   .0541763    .594947     0.09   0.927    -1.111898    1.220251
                               DE  |  -.5886232   .5096561    -1.15   0.248    -1.587531    .4102844
                               FL  |   -.510724   .5916034    -0.86   0.388    -1.670245    .6487973
                               GA  |  -.2274635   .5005662    -0.45   0.650    -1.208555    .7536283
                               HI  |   .1702578   .4979169     0.34   0.732    -.8056415    1.146157
                               ID  |  -2.085057   .7004533    -2.98   0.003     -3.45792   -.7121941
                               IL  |  -.5976584   .5671637    -1.05   0.292    -1.709279     .513962
                               IN  |  -.3657294   .4799424    -0.76   0.446    -1.306399    .5749405
                               IA  |  -3.316278   1.082159    -3.06   0.002    -5.437271   -1.195286
                               KS  |  -1.276077   .6149773    -2.07   0.038     -2.48141   -.0707433
                               KY  |  -1.312366    .692646    -1.89   0.058    -2.669927    .0451949
                               LA  |  -.6626994   .6577935    -1.01   0.314    -1.951951    .6265522
                               ME  |  -.7239045   .6067563    -1.19   0.233    -1.913125     .465316
                               MD  |  -.1195883   .5307078    -0.23   0.822    -1.159756    .9205799
                               MA  |  -.3096418   .5749561    -0.54   0.590    -1.436535    .8172515
                               MI  |  -1.543844   .7823969    -1.97   0.048    -3.077314   -.0103747
                               MN  |  -.3986748   .5288773    -0.75   0.451    -1.435255    .6379056
                               MS  |  -.1576582    .455191    -0.35   0.729    -1.049816    .7344997
                               MO  |  -.8350976   .5193181    -1.61   0.108    -1.852942    .1827472
                               MT  |  -.6070976    .469491    -1.29   0.196    -1.527283    .3130878
                               NE  |  -.5982198   .5150873    -1.16   0.245    -1.607772    .4113328
                               NV  |  -.3092612   .5060416    -0.61   0.541    -1.301085    .6825622
                               NH  |  -1.455801   .5840224    -2.49   0.013    -2.600464   -.3111381
                               NJ  |  -.4155789   .5332017    -0.78   0.436    -1.460635    .6294772
                               NM  |   .2830655   .4824191     0.59   0.557    -.6624586     1.22859
                               NY  |  -.4057351   .5621076    -0.72   0.470    -1.507446    .6959756
                               NC  |  -.2712262   .4520856    -0.60   0.549    -1.157298    .6148452
                               ND  |  -1.089032   .5033172    -2.16   0.030    -2.075516   -.1025488
                               OH  |  -.8408703   .5547779    -1.52   0.130    -1.928215    .2464744
                               OK  |  -.6795451   .5171838    -1.31   0.189    -1.693207    .3341166
                               OR  |  -1.700631    .819408    -2.08   0.038    -3.306641   -.0946204
                               PA  |  -.0920574   .5100428    -0.18   0.857    -1.091723    .9076082
                               RI  |  -.5837534   .5581753    -1.05   0.296    -1.677757    .5102502
                               SC  |   -.165971   .5327526    -0.31   0.755    -1.210147    .8782049
                               SD  |  -.4601434    .459417    -1.00   0.317    -1.360584    .4402975
                               TN  |  -1.570918   .8046374    -1.95   0.051    -3.147978    .0061423
                               TX  |  -.2806936   .5447297    -0.52   0.606    -1.348344     .786957
                               UT  |  -1.131037    .517961    -2.18   0.029    -2.146222    -.115852
                               VT  |  -1.545513   .6347245    -2.43   0.015     -2.78955    -.301476
                               VA  |  -.5815769   .6016576    -0.97   0.334    -1.760804    .5976505
                               WA  |  -.1363871   .5192421    -0.26   0.793    -1.154083    .8813087
                               WV  |   -.775269   .5663308    -1.37   0.171    -1.885257     .334719
                               WI  |  -1.621162   .6537849    -2.48   0.013    -2.902557   -.3397671
                               WY  |  -.6794787   .4639857    -1.46   0.143    -1.588874    .2299165
                                   |
                              year |
                             1984  |  -.5285764   .2150167    -2.46   0.014    -.9500014   -.1071513
                             1988  |  -.5234595    .207591    -2.52   0.012    -.9303304   -.1165887
                             1994  |  -.5032059   .2117475    -2.38   0.017    -.9182235   -.0881884
                             1998  |  -.9167036   .2361937    -3.88   0.000    -1.379635   -.4537725
                             2004  |  -.4531254   .2399868    -1.89   0.059     -.923491    .0172402
                             2008  |  -1.221461   .2987064    -4.09   0.000    -1.806915   -.6360072
                                   |
                             _cons |   2.436335    1.54558     1.58   0.115    -.5929455    5.465616
-----------------------------------+----------------------------------------------------------------
Slight                             |
                      intersection |
                      White Woman  |   .1931054   .0911025     2.12   0.034     .0145478    .3716631
                     Man of Color  |  -.3172519   .1313955    -2.41   0.016    -.5747823   -.0597214
                   Woman of Color  |  -.1812307   .2552353    -0.71   0.478    -.6814826    .3190213
                                   |
                           reve_1c |
                Less than Monthly  |   -.297629   .3278281    -0.91   0.364    -.9401602    .3449022
                          Monthly  |  -.1161711   .3310821    -0.35   0.726      -.76508    .5327378
                           Weekly  |  -.2485277   .3366195    -0.74   0.460    -.9082898    .4112343
                            Daily  |  -.4385847   .3601172    -1.22   0.223    -1.144402    .2672321
                                   |
                           reve_1d |
                Less than Monthly  |   .0999562   .2365576     0.42   0.673    -.3636882    .5636006
                          Monthly  |   -.047279   .2385816    -0.20   0.843    -.5148903    .4203324
                           Weekly  |   -.095447   .2438756    -0.39   0.696    -.5734344    .3825405
                            Daily  |  -.2652661   .2801941    -0.95   0.344    -.8144364    .2839041
                                   |
                     civil_service |
                              Yes  |  -.0358238    .081392    -0.44   0.660    -.1953493    .1237017
                      weekly_hours |   -.001208   .0040723    -0.30   0.767    -.0091895    .0067735
                               age |   .0356844   .0334236     1.07   0.286    -.0298247    .1011934
                             age_2 |  -.0003552   .0003354    -1.06   0.290    -.0010126    .0003023
                                   |
                               edu |
              High school or less  |  -.0919749   .3427269    -0.27   0.788    -.7637072    .5797574
                     Some college  |   .1663849   .1599225     1.04   0.298    -.1470575    .4798274
                   Graduate study  |   .2015898   .1124731     1.79   0.073    -.0188535     .422033
                  Graduate degree  |   .1884617   .0906195     2.08   0.038     .0108507    .3660726
                                   |
                years_employ_state |   .0071847   .0054888     1.31   0.191    -.0035731    .0179426
               years_employ_agency |  -.0004943   .0058017    -0.09   0.932    -.0118654    .0108769
             years_employ_position |   .0013891   .0076752     0.18   0.856    -.0136541    .0164322
                                   |
                              pid5 |
                       Republican  |   .2498545   .1123171     2.22   0.026     .0297171    .4699919
                  Lean Republican  |   .0759571   .1469261     0.52   0.605    -.2120127     .363927
                  Lean Democratic  |   .0029166   .1401706     0.02   0.983    -.2718127    .2776459
                       Democratic  |   .1194994   .1045907     1.14   0.253    -.0854945    .3244933
                                   |
                       agency_size |
                           25-100  |  -.0985542   .1047592    -0.94   0.347    -.3038784      .10677
                          101-500  |  -.0128661   .1183491    -0.11   0.913     -.244826    .2190938
                        501-1,000  |   .0711462    .154941     0.46   0.646    -.2325326     .374825
                      1,001-5,000  |   .0620516   .1636458     0.38   0.705    -.2586883    .3827915
                       Over 5,000  |   .2396354   .2167899     1.11   0.269     -.185265    .6645357
                                   |
                 log_agency_budget |  -.0130779   .0271604    -0.48   0.630    -.0663113    .0401554
                      inst6017_nom |   .0006121   .0040558     0.15   0.880    -.0073371    .0085612
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.2549457    .212338    -1.20   0.230    -.6711206    .1612292
                Staff: Non-Fiscal  |  -.2889992   .2214988    -1.30   0.192    -.7231288    .1451304
Income Security & Social Services  |  -.3139752   .2033325    -1.54   0.123    -.7124996    .0845491
                        Education  |  -.3345463   .2215776    -1.51   0.131    -.7688304    .0997377
                           Health  |  -.2827446   .2154162    -1.31   0.189    -.7049525    .1394634
                Natural Resources  |  -.3408905   .1922803    -1.77   0.076    -.7177528    .0359719
             Environment & Energy  |  -.4688997   .2016218    -2.33   0.020    -.8640712   -.0737283
             Economic Development  |  -.1958207   .2044276    -0.96   0.338    -.5964914    .2048501
                 Criminal Justice  |  -.1134698   .2018796    -0.56   0.574    -.5091466    .2822069
                       Regulatory  |  -.1317981   .1908645    -0.69   0.490    -.5058857    .2422895
                   Transportation  |  -.4605179   .2185867    -2.11   0.035    -.8889399   -.0320958
                            Other  |  -.2868649   .2050736    -1.40   0.162    -.6888019     .115072
                                   |
                             state |
                               AK  |  -.1110527   .2987061    -0.37   0.710     -.696506    .4744005
                               AZ  |   .1405429   .3163309     0.44   0.657    -.4794543      .76054
                               AR  |  -.7030017   .3419297    -2.06   0.040    -1.373172   -.0328318
                               CA  |   -.009462   .3245934    -0.03   0.977    -.6456533    .6267293
                               CO  |   .1083198   .2931142     0.37   0.712    -.4661734    .6828131
                               CT  |  -.7461931   .4034302    -1.85   0.064    -1.536902    .0445156
                               DE  |  -.0241489   .3077492    -0.08   0.937    -.6273262    .5790283
                               FL  |  -.3358405   .3258297    -1.03   0.303    -.9744549    .3027739
                               GA  |  -.1465902   .3058805    -0.48   0.632     -.746105    .4529245
                               HI  |    .312427   .3194981     0.98   0.328    -.3137779    .9386318
                               ID  |  -.2341008   .3095778    -0.76   0.450    -.8408621    .3726605
                               IL  |  -.4003174   .3408384    -1.17   0.240    -1.068348    .2677136
                               IN  |  -.1617015   .3137702    -0.52   0.606    -.7766797    .4532767
                               IA  |  -.8177759   .3033016    -2.70   0.007    -1.412236   -.2233157
                               KS  |  -.1594266    .315603    -0.51   0.613    -.7779972     .459144
                               KY  |  -.7982937   .3418624    -2.34   0.020    -1.468332   -.1282557
                               LA  |   .0200808   .3346946     0.06   0.952    -.6359085    .6760702
                               ME  |   .0505133    .323583     0.16   0.876    -.5836977    .6847244
                               MD  |  -.2565998   .3165204    -0.81   0.418    -.8769684    .3637689
                               MA  |    -.27887   .3273374    -0.85   0.394    -.9204395    .3626995
                               MI  |  -.3939444   .3255212    -1.21   0.226    -1.031954    .2440654
                               MN  |   .0614868   .2905171     0.21   0.832    -.5079163    .6308899
                               MS  |  -.3958789   .3194549    -1.24   0.215    -1.021999    .2302411
                               MO  |   -.072186   .2941233    -0.25   0.806    -.6486571    .5042852
                               MT  |   .0997507   .2845607     0.35   0.726     -.457978    .6574793
                               NE  |   .2406174   .3043579     0.79   0.429    -.3559131    .8371479
                               NV  |   -.220146   .3089185    -0.71   0.476    -.8256152    .3853231
                               NH  |  -.6815846   .3449729    -1.98   0.048    -1.357719   -.0054502
                               NJ  |   -.326044   .3268392    -1.00   0.318     -.966637    .3145491
                               NM  |   .5235733   .3225473     1.62   0.105    -.1086078    1.155754
                               NY  |  -.4246594   .3707751    -1.15   0.252    -1.151365    .3020464
                               NC  |  -.1086878   .2870406    -0.38   0.705    -.6712771    .4539015
                               ND  |  -.0168033   .2961837    -0.06   0.955    -.5973127    .5637062
                               OH  |  -.2258414   .3079669    -0.73   0.463    -.8294454    .3777625
                               OK  |  -.5028335   .3165059    -1.59   0.112    -1.123174    .1175068
                               OR  |   .1901156   .2992265     0.64   0.525    -.3963576    .7765888
                               PA  |   -.088561    .308927    -0.29   0.774    -.6940467    .5169248
                               RI  |   .0705929    .323623     0.22   0.827    -.5636966    .7048824
                               SC  |  -.0985969   .3491242    -0.28   0.778    -.7828677     .585674
                               SD  |  -.0310379   .3100202    -0.10   0.920    -.6386664    .5765906
                               TN  |  -.4553924   .3257422    -1.40   0.162    -1.093835    .1830505
                               TX  |  -.1851055   .3319583    -0.56   0.577    -.8357318    .4655209
                               UT  |  -.0385934   .2943744    -0.13   0.896    -.6155567    .5383699
                               VT  |  -.6401209   .3229333    -1.98   0.047    -1.273059   -.0071832
                               VA  |   .0359084   .3338692     0.11   0.914    -.6184632    .6902801
                               WA  |  -.0699178   .2990982    -0.23   0.815    -.6561395     .516304
                               WV  |  -1.040264   .3477999    -2.99   0.003    -1.721939   -.3585887
                               WI  |  -.7433158   .3180142    -2.34   0.019    -1.366612   -.1200194
                               WY  |  -.1365729   .2961266    -0.46   0.645    -.7169703    .4438245
                                   |
                              year |
                             1984  |  -.1254798   .1215138    -1.03   0.302    -.3636425    .1126829
                             1988  |  -.0681856   .1150611    -0.59   0.553    -.2937012    .1573301
                             1994  |    -.40227   .1236657    -3.25   0.001    -.6446503   -.1598897
                             1998  |  -.5180192   .1332519    -3.89   0.000    -.7791881   -.2568503
                             2004  |  -.2018137   .1360086    -1.48   0.138    -.4683858    .0647583
                             2008  |  -.5457735   .1470644    -3.71   0.000    -.8340144   -.2575326
                                   |
                             _cons |  -.3536101   .9487088    -0.37   0.709    -2.213045    1.505825
-----------------------------------+----------------------------------------------------------------
Moderate                           |  (base outcome)
-----------------------------------+----------------------------------------------------------------
High                               |
                      intersection |
                      White Woman  |   .0440057   .1006857     0.44   0.662    -.1533346    .2413461
                     Man of Color  |   .1584426   .1310608     1.21   0.227    -.0984319    .4153171
                   Woman of Color  |   .5753669    .226474     2.54   0.011      .131486    1.019248
                                   |
                           reve_1c |
                Less than Monthly  |  -.4459402   .3199304    -1.39   0.163    -1.072992    .1811117
                          Monthly  |  -.4042144   .3242006    -1.25   0.212    -1.039636    .2312071
                           Weekly  |  -.4561308   .3327556    -1.37   0.170     -1.10832    .1960581
                            Daily  |  -.5963898   .3578929    -1.67   0.096    -1.297847    .1050674
                                   |
                           reve_1d |
                Less than Monthly  |   .2030139   .2680226     0.76   0.449    -.3223007    .7283285
                          Monthly  |    .239482   .2712833     0.88   0.377    -.2922235    .7711875
                           Weekly  |   .2777453   .2782552     1.00   0.318    -.2676247    .8231154
                            Daily  |   .4851151   .3077392     1.58   0.115    -.1180426    1.088273
                                   |
                     civil_service |
                              Yes  |   .0632999   .0874298     0.72   0.469    -.1080592    .2346591
                      weekly_hours |   .0017732    .004355     0.41   0.684    -.0067624    .0103088
                               age |   .0068649   .0324415     0.21   0.832    -.0567193    .0704492
                             age_2 |   .0000189   .0003219     0.06   0.953     -.000612    .0006498
                                   |
                               edu |
              High school or less  |   .4089992   .3129353     1.31   0.191    -.2043426    1.022341
                     Some college  |  -.0628759    .163315    -0.38   0.700    -.3829673    .2572156
                   Graduate study  |   .0108838   .1148016     0.09   0.924    -.2141233    .2358909
                  Graduate degree  |  -.1977874    .092681    -2.13   0.033    -.3794388   -.0161361
                                   |
                years_employ_state |  -.0042184   .0059338    -0.71   0.477    -.0158485    .0074117
               years_employ_agency |   .0125696   .0062527     2.01   0.044     .0003146    .0248246
             years_employ_position |  -.0085362   .0083067    -1.03   0.304     -.024817    .0077446
                                   |
                              pid5 |
                       Republican  |     .19353   .1184696     1.63   0.102    -.0386662    .4257263
                  Lean Republican  |   .2112893   .1539374     1.37   0.170    -.0904224     .513001
                  Lean Democratic  |   .0635601   .1482564     0.43   0.668    -.2270171    .3541373
                       Democratic  |   .0928747   .1102399     0.84   0.400    -.1231915    .3089408
                                   |
                       agency_size |
                           25-100  |  -.0796278   .1071074    -0.74   0.457    -.2895543    .1302988
                          101-500  |  -.0446499   .1243843    -0.36   0.720    -.2884388    .1991389
                        501-1,000  |  -.2803132   .1699149    -1.65   0.099    -.6133402    .0527138
                      1,001-5,000  |  -.3122494   .1719852    -1.82   0.069    -.6493342    .0248353
                       Over 5,000  |  -.2014075   .2365093    -0.85   0.394    -.6649573    .2621423
                                   |
                 log_agency_budget |  -.0135438   .0291429    -0.46   0.642    -.0706628    .0435752
                      inst6017_nom |    .003015   .0042384     0.71   0.477    -.0052922    .0113221
                                   |
                          funcat13 |
                    Staff: Fiscal  |  -.3520702     .21882    -1.61   0.108    -.7809495    .0768091
                Staff: Non-Fiscal  |  -.1545559    .223088    -0.69   0.488    -.5918002    .2826885
Income Security & Social Services  |   -.514735   .2097348    -2.45   0.014    -.9258077   -.1036624
                        Education  |  -.4555453   .2319942    -1.96   0.050    -.9102456    -.000845
                           Health  |   -.359459   .2234217    -1.61   0.108    -.7973575    .0784395
                Natural Resources  |  -.4261568   .1973025    -2.16   0.031    -.8128626    -.039451
             Environment & Energy  |  -.3384106   .2026145    -1.67   0.095    -.7355277    .0587065
             Economic Development  |  -.3939851   .2112157    -1.87   0.062    -.8079603    .0199902
                 Criminal Justice  |   -.408241   .2139006    -1.91   0.056    -.8274784    .0109964
                       Regulatory  |  -.4475014   .1965566    -2.28   0.023    -.8327452   -.0622577
                   Transportation  |  -.3620429   .2225965    -1.63   0.104    -.7983239    .0742382
                            Other  |  -.1991114   .2067546    -0.96   0.336    -.6043429    .2061201
                                   |
                             state |
                               AK  |  -.1213028   .3595982    -0.34   0.736    -.8261024    .5834968
                               AZ  |   .3747858   .3753902     1.00   0.318    -.3609654    1.110537
                               AR  |     .45121   .3485092     1.29   0.195    -.2318556    1.134276
                               CA  |   .0384826   .3885707     0.10   0.921    -.7231019    .8000671
                               CO  |  -.0402995   .3618316    -0.11   0.911    -.7494763    .6688774
                               CT  |   .6751274   .3919299     1.72   0.085    -.0930412    1.443296
                               DE  |   .0907284   .3637534     0.25   0.803    -.6222153     .803672
                               FL  |   .4094755   .3661316     1.12   0.263    -.3081292     1.12708
                               GA  |   .1035124   .3695226     0.28   0.779    -.6207386    .8277635
                               HI  |  -.1384272   .3906372    -0.35   0.723     -.904062    .6272076
                               ID  |   .5784869   .3457086     1.67   0.094    -.0990895    1.256063
                               IL  |  -.0301672   .3944517    -0.08   0.939    -.8032782    .7429439
                               IN  |   .1425247   .3708084     0.38   0.701    -.5842464    .8692958
                               IA  |   .1275465   .3330927     0.38   0.702    -.5253032    .7803963
                               KS  |   .9662545   .3396679     2.84   0.004     .3005177    1.631991
                               KY  |   .5900101   .3465348     1.70   0.089    -.0891856    1.269206
                               LA  |   .4661638   .3785036     1.23   0.218    -.2756897    1.208017
                               ME  |   .2459382   .3745062     0.66   0.511    -.4880805     .979957
                               MD  |   .5913066    .347372     1.70   0.089    -.0895301    1.272143
                               MA  |  -1.252537   .5196094    -2.41   0.016    -2.270953   -.2341213
                               MI  |   .7229411   .3394442     2.13   0.033     .0576428    1.388239
                               MN  |   .0191678   .3578157     0.05   0.957    -.6821381    .7204736
                               MS  |    .356133    .354783     1.00   0.315     -.339229    1.051495
                               MO  |   .0298431     .35175     0.08   0.932    -.6595742    .7192604
                               MT  |  -.0769508   .3531169    -0.22   0.827    -.7690472    .6151455
                               NE  |   .3568912   .3579318     1.00   0.319    -.3446422    1.058425
                               NV  |   .2663826   .3553359     0.75   0.453    -.4300629    .9628281
                               NH  |   .6968599   .3504431     1.99   0.047     .0100041    1.383716
                               NJ  |   .2099864   .3713307     0.57   0.572    -.5178085    .9377812
                               NM  |   .0836396   .4017426     0.21   0.835    -.7037614    .8710407
                               NY  |  -.3208387   .4472303    -0.72   0.473    -1.197394    .5557167
                               NC  |   .4923408   .3314326     1.49   0.137    -.1572552    1.141937
                               ND  |   .0372027   .3584249     0.10   0.917    -.6652972    .7397025
                               OH  |    .526795    .343952     1.53   0.126    -.1473386    1.200929
                               OK  |   .5761296   .3351569     1.72   0.086    -.0807659    1.233025
                               OR  |  -.0674065   .3793797    -0.18   0.859    -.8109771    .6761641
                               PA  |     .24146   .3613473     0.67   0.504    -.4667676    .9496876
                               RI  |  -.1249861   .4125732    -0.30   0.762    -.9336147    .6836425
                               SC  |   1.307201   .3583786     3.65   0.000     .6047923     2.00961
                               SD  |    .238211   .3662778     0.65   0.515    -.4796803    .9561022
                               TN  |   .4892328   .3551645     1.38   0.168    -.2068768    1.185342
                               TX  |   .7116582   .3611443     1.97   0.049     .0038284    1.419488
                               UT  |   .3860174   .3394661     1.14   0.255    -.2793239    1.051359
                               VT  |   .2487935   .3504074     0.71   0.478    -.4379924    .9355795
                               VA  |   .4787785   .3833785     1.25   0.212    -.2726296    1.230187
                               WA  |  -.5494796   .3939016    -1.39   0.163    -1.321513    .2225535
                               WV  |   .5293269   .3404098     1.55   0.120     -.137864    1.196518
                               WI  |   .2790964   .3343426     0.83   0.404     -.376203    .9343958
                               WY  |    .294355   .3417626     0.86   0.389    -.3754874    .9641975
                                   |
                              year |
                             1984  |  -.6035551    .129688    -4.65   0.000     -.857739   -.3493713
                             1988  |  -.4992408   .1224559    -4.08   0.000      -.73925   -.2592315
                             1994  |   -.377422   .1256017    -3.00   0.003    -.6235967   -.1312472
                             1998  |  -.3657484   .1337493    -2.73   0.006    -.6278921   -.1036047
                             2004  |  -.5514277   .1474916    -3.74   0.000     -.840506   -.2623494
                             2008  |  -.4487024   .1514133    -2.96   0.003     -.745467   -.1519379
                                   |
                             _cons |  -.2792973   .9505463    -0.29   0.769    -2.142334    1.583739
----------------------------------------------------------------------------------------------------

. 
. est sto mlogit8

. 
.  esttab mlogit8 using Table_B15.rtf  ,starlevels(+ 0.10 * 0.05 ** 0.01) cells(b(star fmt(3)) se(par fmt(3))
> ) ///
>  stats(N aic bic, labels("N. of observations" "AIC" "BIC" )) ///
>  label varwidth(35) ti("") ///
>  mtitles("Legis. Regs." ) 
(output written to Table_B15.rtf)

. 
. 
end of do-file

